Newborn auditory brainstem response and sudden infant death syndrome.

Sudden infant death syndrome (SIDS)-the sudden and unexplained death of a seemingly healthy infant, <1 year old-may be associated with abnormalities in the brain regions that underlie breathing and arousal during sleep. While post-mortem studies suggest abnormalities in SIDS infants' brainstems, there are no studies of these infants' brainstem function before death. One way to assess the function of the brainstem is with auditory brainstem response (ABR), a routine hearing-screening method that noninvasively measures the brainstem's response to sound. We hypothesize that anomalies in newborns' ABR measures may predict SIDS. Indeed, previous studies identified abnormalities in ABR characteristics in small samples of near-miss SIDS infants hospitalized for infant apnea syndrome. However, there is a need to examine the ABRs of infants who died of SIDS. Therefore, in the current study, we propose integrating two secondary datasets to examine newborns' ABRs (N = 156,972), including those who later died of SIDS (n = ~42; .27 out of every 1000 infants), using existing archived records of neonatal ABR results from a sample of newborns born in Florida. We hypothesize that infants who die from SIDS are more likely than non-SIDS infants to have abnormal ABRs as newborns. Understanding the association between SIDS and ABR may facilitate more accurate identification of an infant's risk for SIDS at birth, enabling increased monitoring, which may facilitate interventions and improve survivorship.

Infants' salivary oxytocin and positive affective reactions to people.

Oxytocin is a neuropeptide positively associated with prosociality in adults. Here, we studied whether infants' salivary oxytocin can be reliably measured, is developmentally stable, and is linked to social behavior. We longitudinally collected saliva from 62 U.S. infants (44 % female, 56 % Hispanic/Latino, 24 % Black, 18 % non-Hispanic White, 11 % multiracial) at 4, 8, and 14 months of age and offline-video-coded the valence of their facial affect in response to a video of a smiling woman. We also captured infants' affective reactions in terms of excitement/joyfulness during a live, structured interaction with a singing woman in the Early Social Communication Scales at 14 months. We detected stable individual differences in infants' oxytocin levels over time (over minutes and months) and in infants' positive affect over months and across contexts (video-based and in live interactions). We detected no statistically significant changes in oxytocin levels between 4 and 8 months but found an increase from 8 to 14 months. Infants with higher oxytocin levels showed more positive facial affect to a smiling person video at 4 months; however, this association disappeared at 8 months, and reversed at 14 months (i.e., higher oxytocin was associated with less positive facial affect). Infant salivary oxytocin may be a reliable physiological measure of individual differences related to socio-emotional development.

Infection detection in faces: Children's development of pathogen avoidance.

This study examined the development of children's avoidance and recognition of sickness using face photos from people with natural, acute, contagious illness. In a U.S. sample of fifty-seven 4- to 5-year-olds (46% male, 70% White), fifty-two 8- to 9-year-olds (26% male, 62% White), and 51 adults (59% male, 61% White), children and adults avoided and recognized sick faces (ds ranged from 0.38 to 2.26). Both avoidance and recognition improved with age. Interestingly, 4- to 5-year-olds' avoidance of sick faces positively correlated with their recognition, suggesting stable individual differences in these emerging skills. Together, these findings are consistent with a hypothesized immature but functioning and flexible behavioral immune system emerging early in development. Characterizing children's sickness perception may help design interventions to improve health.

JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles.

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS).

The number of papers presenting machine learning (ML) models that are being submitted to and published in the Journal of Medical Internet Research and other JMIR Publications journals has steadily increased. Editors and peer reviewers involved in the review process for such manuscripts often go through multiple review cycles to enhance the quality and completeness of reporting. The use of reporting guidelines or checklists can help ensure consistency in the quality of submitted (and published) scientific manuscripts and, for example, avoid instances of missing information. In this Editorial, the editors of JMIR Publications journals discuss the general JMIR Publications policy regarding authors' application of reporting guidelines and specifically focus on the reporting of ML studies in JMIR Publications journals, using the Consolidated Reporting of Machine Learning Studies (CREMLS) guidelines, with an example of how authors and other journals could use the CREMLS checklist to ensure transparency and rigor in reporting.

Behavioral and physiological sensitivity to natural sick faces.

The capacity to rapidly detect and avoid sick people may be adaptive. Given that faces are reliably available, as well as rapidly detected and processed, they may provide health information that influences social interaction. Prior studies used faces that were manipulated to appear sick (e.g., editing photos, inducing inflammatory response); however, responses to naturally sick faces remain largely unexplored. We tested whether adults detected subtle cues of genuine, acute, potentially contagious illness in face photos compared to the same individuals when healthy. We tracked illness symptoms and severity with the Sickness Questionnaire and Common Cold Questionnaire. We also checked that sick and healthy photos were matched on low-level features. We found that participants (N = 109) rated sick faces, compared to healthy faces, as sicker, more dangerous, and eliciting more unpleasant feelings. Participants (N = 90) rated sick faces as more likely to be avoided, more tired, and more negative in expression than healthy faces. In a passive-viewing eye-tracking task, participants (N = 50) looked longer at healthy than sick faces, especially the eye region, suggesting people may be more drawn to healthy conspecifics. When making approach-avoidance decisions, participants (N = 112) had greater pupil dilation to sick than healthy faces, and more pupil dilation was associated with greater avoidance, suggesting elevated arousal to threat. Across all experiments, participants' behaviors correlated with the degree of sickness, as reported by the face donors, suggesting a nuanced, fine-tuned sensitivity. Together, these findings suggest that humans may detect subtle threats of contagion from sick faces, which may facilitate illness avoidance. By better understanding how humans naturally avoid illness in conspecifics, we may identify what information is used and ultimately improve public health.

Best Practices for Using AI Tools as an Author, Peer Reviewer, or Editor.

The ethics of generative artificial intelligence (AI) use in scientific manuscript content creation has become a serious matter of concern in the scientific publishing community. Generative AI has computationally become capable of elaborating research questions; refining programming code; generating text in scientific language; and generating images, graphics, or figures. However, this technology should be used with caution. In this editorial, we outline the current state of editorial policies on generative AI or chatbot use in authorship, peer review, and editorial processing of scientific and scholarly manuscripts. Additionally, we provide JMIR Publications' editorial policies on these issues. We further detail JMIR Publications' approach to the applications of AI in the editorial process for manuscripts in review in a JMIR Publications journal.

Social motivation predicts gaze following between 6 and 14 months.

Infants vary in their ability to follow others' gazes, but it is unclear how these individual differences emerge. We tested whether social motivation levels in early infancy predict later gaze following skills. We longitudinally tracked infants' (N = 82) gazes and pupil dilation while they observed videos of a woman looking into the camera simulating eye contact (i.e., mutual gaze) and then gazing toward one of two objects, at 2, 4, 6, 8, and 14 months of age. To improve measurement validity, we used confirmatory factor analysis to combine multiple observed measures to index the underlying constructs of social motivation and gaze following. Infants' social motivation-indexed by their speed of social orienting, duration of mutual gaze, and degree of pupil dilation during mutual gaze-was developmentally stable and positively predicted the development of gaze following-indexed by their proportion of time looking to the target object, first object look difference scores, and first face-to-object saccade difference scores-from 6 to 14 months of age. These findings suggest that infants' social motivation likely plays a role in the development of gaze following and highlight the use of a multi-measure approach to improve measurement sensitivity and validity in infancy research.

Telehealth Competencies in Medical Education: New Frontiers in Faculty Development and Learner Assessments.

Telehealth visits have become an integral model of healthcare delivery since the COVID-19 pandemic. This rapid expansion of telehealthcare delivery has forced faculty development and trainee education in telehealth to occur simultaneously. In response, academic medical institutions have quickly implemented clinical training to teach digital health skills to providers across the medical education continuum. Yet, learners of all levels must still receive continual assessment and feedback on their skills to align with the telehealth competencies and milestones set forth by the Association of American Medical Colleges (AAMC) and the Accreditation Council for Graduate Medical Education (ACGME). This paper discusses key educational needs and emerging areas for faculty development in telehealth teaching and assessment of telehealth competencies. It proposes strategies for the successful integration of the AAMC telehealth competencies and ACGME milestones into medical education, including skills in communication, data gathering, and patient safety with appropriate telehealth use. Direct observation tools in the paper offer educators novel instruments to assess telehealth competencies in medical students, residents, and peer faculty. The integration of AAMC and ACGME telehealth competencies and the new assessment tools in this paper provide a unique perspective to advance clinical practice and teaching skills in telehealthcare delivery.

Brilliant Ideas Can Come in All Sizes: Research Letters.

The Journal of Medical Internet Research is pleased to offer "Research Letter" as a new article type. Research Letters are similar to original and short paper types in that they report the original results of studies in a peer-reviewed, structured scientific communication. The Research Letter article type is optimal for presenting new, early, or sometimes preliminary research findings, including interesting observations from ongoing research with significant implications that justify concise and rapid communication.

Infant temperamental fear, pupil dilation, and gaze aversion from smiling strangers.

In childhood, higher levels of temperamental fear-an early-emerging proclivity to distress in the face of novelty-are associated with lower social responsivity and greater social anxiety. While the early emergence of temperamental fear in infancy is poorly understood, it is theorized to be driven by individual differences in reactivity and self-regulation to novel stimuli. The current study used eye tracking to capture infants' (N = 124) reactions to a video of a smiling stranger-a common social encounter-including infant gaze aversions from the stranger's face (indexing arousal regulation) and pupil dilation (indexing physiological reactivity), longitudinally at 2, 4, 6, and 8 months of age. Multilevel mixed-effects models indicated that more fearful infants took more time to look away from a smiling stranger's face than less fearful infants, suggesting that high-fear infants may have slower arousal regulation. At 2 and 4 months, more fearful infants also exhibited greater and faster pupil dilation before gaze aversions, consistent with greater physiological reactivity. Together, these findings suggest that individual differences in infants' gaze aversions and pupil dilation can index the development of fearful temperament in early infancy, facilitating the identification of, and interventions for, risk factors to social disruptions.

A Survey to Assess the Need for a National Registry to Track Physician Suicide.

Physician suicide is a growing public health crisis that affects the medical community and patients. Literature on physician suicide has been published since 1903. However, the epidemiology of physician suicide including incidence is unclear due to a lack of accurate data. Lack of reliable data can lead to barriers in developing effective physician suicide prevention programs and creating policies to address the issue. Data are often collected from multiple data sources that each have limitations resulting in crude estimates of incidence and persistent barriers to surveillance. The aim of this study was to survey the medical community to determine the perceived usefulness of a physician suicide registry, with an accompanying data warehouse, to collect and store information about suicides reported from the community. Physicians at all stages of their training and careers would be key stakeholders contributing information to the registry and therefore their perception of such a tool to track physician suicides is important. Results show that 70.0% of respondents expressed that they somewhat to strongly agree with the approach; and 74.2% agreed with a statement that more research is needed on physician suicide. The proposed registry to better track physician suicide is a possible solution to better address physician suicide that has garnered initial support from the medical community as reflected by the survey results.

Evaluating the Effectiveness of Social Distancing Interventions to Delay or Flatten the Epidemic Curve of Coronavirus Disease.

By April 2, 2020, >1 million persons worldwide were infected with severe acute respiratory syndrome coronavirus 2. We used a mathematical model to investigate the effectiveness of social distancing interventions in a mid-sized city. Interventions reduced contacts of adults >60 years of age, adults 20-59 years of age, and children <19 years of age for 6 weeks. Our results suggest interventions started earlier in the epidemic delay the epidemic curve and interventions started later flatten the epidemic curve. We noted that, while social distancing interventions were in place, most new cases, hospitalizations, and deaths were averted, even with modest reductions in contact among adults. However, when interventions ended, the epidemic rebounded. Our models suggest that social distancing can provide crucial time to increase healthcare capacity but must occur in conjunction with testing and contact tracing of all suspected cases to mitigate virus transmission.

Facilitating credentialing and engagement of international physician-migrants during the COVID-19 crisis and beyond.

CONTEXT: Physicians who migrate globally face a daunting series of time-consuming, labor- and resource-intensive procedures to prove their clinical competency before being allowed to practice medicine in a new country. ISSUES: In this commentary, we describe licensing barriers faced by physician-migrants based on the authors' experiences, and reflect also on rapidly implemented measures to address COVID-19 pandemic related workforce shortages. We offer recommendations for potential reductions in bureaucratic regulatory barriers that prohibit mobilization of international medical graduate talent. LESSONS LEARNED: Licensing boards and authorities should strive for standardized, competency-based basic professional recognition. Professional medical societies are well-positioned to guide such competency-based recognition as a more organized, international collaborative effort across specialties. The COVID-19 pandemic facilitated cross-state and international licensing in some regions, highlighting a key opportunity: streamlining professional recognition requirements is achievable.

Healthcare Service Utilization under a New Virtual Primary Care Delivery Model.

Background:Telemedicine holds great promise for changing healthcare delivery. While telemedicine has been used significantly in the direct-to-consumer setting, the use of telemedicine in a preventive primary care setting is not well studied.Introduction:ClickWell Care (CWC) is the first known implementation of a technology-enabled primary care model. We wanted to quantify healthcare utilization of primary care by patient characteristics and modality of care delivery.Materials and Methods:Our study population included those who completed a visit to a CWC clinic between January 1, 2015 and September 30, 2015. We compared patients based on utilization of CWCs in-person and virtual visits across the following domains: patient demographics, distance from clinic, responses to a Health Risk Assessment, and top 10 conditions treated.Results:Thousand two hundred seven patients completed a visit with a CWC physician in 2015. Nearly three-quarters of our patients were ≤40 years and sex was significantly different (p = 0.015) between visit cohorts. The greatest representation of men (47%) was seen in the virtual-only cohort. Patients' proximity to the clinic was also significantly different across visit cohorts (p = 0.018) with 44% of in-person-only and 34% of virtual-only patients living within 5 miles of Stanford Hospital.Discussion:We found men were more likely to engage in virtual-only care. Young patients are willing to accept virtual care although many prefer to complete an in-person visit first.Conclusions:Our findings suggest that a "bricks-and-clicks" care model where telemedicine is supported by a brick-and-mortar location may be an effective way to leverage telemedicine to deliver primary care.

Periodic solutions in an SIRWS model with immune boosting and cross-immunity.

Incidence of whooping cough, an infection caused by Bordetella pertussis and Bordetella parapertussis, has been on the rise since the 1980s in many countries. Immunological interactions, such as immune boosting and cross-immunity between pathogens, have been hypothesised to be important drivers of epidemiological dynamics. We present a two-pathogen model of transmission which examines how immune boosting and cross-immunity can influence the timing and severity of epidemics. We use a combination of numerical simulations and bifurcation techniques to study the dynamical properties of the system, particularly the conditions under which stable periodic solutions are present. We derive analytic expressions for the steady state of the single-pathogen model, and give a condition for the presence of periodic solutions. A key result from our two-pathogen model is that, while studies have shown that immune boosting at relatively strong levels can independently generate periodic solutions, cross-immunity allows for the presence of periodic solutions even when the level of immune boosting is weak. Asymmetric cross-immunity can produce striking increases in the incidence and period. Our study underscores the importance of developing a better understanding of the immunological interactions between pathogens in order to improve model-based interpretations of epidemiological data.