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An extensive archaeological dental calculus dataset spanning 5000 years for ancient human oral microbiome research
No full textArchaeological dental calculus can provide detailed insights into the ancient human oral microbiome. We offer a multi-period, multi-site, ancient shotgun metagenomic dataset consisting of 174 samples obtained primarily from archaeological dental calculus derived from various skeletal collections in the United Kingdom. This article describes all the materials used including the skeletons' historical period and burial location, biological sex, and age determination, data accessibility, and additional details associated with environmental and laboratory controls. In addition, this article describes the laboratory and bioinformatic methods associated with the dataset development and discusses the technical validity of the data following quality assessments, damage evaluations, and decontamination procedures. Our approach to collecting, making accessible, and evaluating bioarchaeological metadata in advance of metagenomic analysis aims to further enable the exploration of archaeological science topics such as diet, disease, and antimicrobial resistance (AMR)
Hidden Bias, Overt Impact: A Systematic Review of the Empirical Literature on Racial Microaggressions at Work
No full textAbstract
This article presents a systematic review of literature on workplace racial microaggressions. Increasingly, workplaces around the world have made concerted efforts to foster diversity, equity, and inclusion in their workforces. However, racial discrimination is a social issue that continues to be endemic to the workplace—including, yet not limited to, the prevalence of racial microaggressions. These microaggressions can, at times, be covert, and undertaken sometimes without the explicit awareness or intention of the perpetrator. Yet, the consequences of these can be very real for the person impacted (the target), which include diminished wellbeing, job satisfaction, and career progression. To capture the overall trends and themes that empirical research has examined related to workplace racial microaggressions, a systematic review of 48 scholarly peer-reviewed articles on the topic was conducted. The review highlights how racial microaggressions have been conceptualized and measured in previous work, and critically examines empirical findings to date. The systematic review reveals that more work needs to be done to advance our understanding of this field of inquiry. To address this, a future research agenda based on identified gaps in the literature is articulated which highlights opportunities for advancement of the literature. Addressing these gaps will provide actionable insights for organizations in addressing the insidious social issue of racial microaggressions in the workplace, and support scholars in the development of future work
Early environmental conditions do not impact behavioural flexibility in an invasive and noninvasive lizard species
No full textBehavioural flexibility, the ability to adjust behaviour adaptively in response to internal or external changes, is expected to be crucial for animals adapting to environmental fluctuations. However, conditions experienced during early development can profoundly impact behavioural flexibility, making it unclear how populations will respond to novel circumstances. Stressful situations faced by the parents can have a direct impact on offspring cognition through the transmission of glucocorticoids, stress-related hormones that affect offspring cognition. At the same time, stressful conditions can influence parental behaviours during nesting and, consequently, the thermal developmental conditions that offspring experience. Here, we investigated the interactive effects of prenatal corticosterone (CORT) levels and temperature on behavioural flexibility in two lizard species: Lampropholis delicata and Lampropholis guichenoti. We manipulated prenatal CORT levels and incubation temperature in a 2 × 2 factorial design and then assessed behavioural flexibility through a reversal learning task. We hypothesized that prenatal CORT levels and cold temperatures would impair performance in the reversal task. We expected L. delicata, given its success as an invasive species, to show more flexibility and be less susceptible to early environmental conditions. Contrary to our expectations, behavioural flexibility appears robust to prenatal temperatures and CORT levels in both species. The lack of difference in reversal learning between L. delicata and L. guichenoti suggests that novel environments are unlikely to influence flexible behavioural learning, and behavioural flexibility itself is unlikely to explain differences in invasion success between these species
A new pile-soil interface and its application in battered mini piles under monotonic lateral load in cohesive soil
No full textNumerical modelling of laterally loaded piles requires a robust pile-soil interface model. The conventional Coulomb friction model has limitations when predicting the soil-structure interaction at shallow depths for battered mini piles (BMPs) in cohesive (fine-grained) soils. This paper proposes an efficient pile-soil interface model to simulate laterally loaded BMPs in cohesive soils using three-dimensional finite element models (FEM). BMP systems have been commonly used to support lateral load-dominated lightweight superstructures. They are hybrid foundations with BMPs oriented at different inclinations and directions, mimicking tree root systems. FEM results indicate that the Coulomb model is unsuitable for simulating the pile-soil interface at shallow depth due to underprediction of shear resistance. The proposed interface model comprising a surface-to-surface cohesive damage interface with friction captures the lateral performance of BMPs accurately. The proposed model was implemented for a range of pile and soil properties to verify its suitability in understanding the behaviour of BMPs. The ultimate lateral capacity of BMPs increases with penetration length up to 1.5 m. While an increase in diameter and undrained shear strength increases the capacity, the lateral load eccentricity negatively impacts it. Interaction diagrams are developed to serve engineers estimate the ultimate lateral capacity of BMPs
Artificial intelligence-driven closed-loop devices in sudden unexpected death in epilepsy prediction and prevention: Insights from persons with epilepsy and caregivers
No full textOBJECTIVE: The absence of strategies for predicting and preventing sudden unexpected death in epilepsy (SUDEP) is intertwined with the lack of studies measuring users' attitudes toward potential innovative interventions. The NEUROSENSE Project (http://www.neurosense-project.eu) aims to evaluate novel SUDEP-predictive neuroendocrine biomarkers in interstitial fluid. The ultimate aim is to develop an artificial intelligence-driven closed loop device (AI-CLD) prototype that can recognize life-threatening seizures and prevent SUDEP through automatic intervention. The current study introduces the potential use of AI-CLDs in SUDEP prediction and prevention, while assessing person with epilepsy (PWE) and caregiver (CG) attitudes toward AI-CLD adoption and implementation. METHODS: A qualitative study was conducted through three focus groups involving PWEs and CGs. Participants were recruited through the NEUROSENSE Patient Advisory Board, with discussions facilitated through a semistructured interview guide. The study followed grounded theory and qualitative content analysis methods. Data were collected between October 2024 and February 2025, with all sessions transcribed and analyzed. RESULTS: Three main areas emerged from the analysis: expectations of AI-CLDs for SUDEP prediction and prevention, decision-making processes involving AI use in health care, and barriers and facilitators to AI-CLD adoption. PWEs and CGs generally expressed positive attitudes toward AI-CLDs, supporting automatic data sharing with health care providers and real-time alerts. However, concerns about AI accuracy, overreliance on automation, and the need for control over interventions were raised. Both groups preferred wearable devices over implanted solutions, emphasizing comfort and discretion as critical factors for adoption. SIGNIFICANCE: This study highlights the potential of AI-CLDs in improving the prediction and prevention of SUDEP, showing promise for enhancing patient safety through real-time monitoring and interventions. The findings underscore the importance of user-centered design in device development, emphasizing comfort, control over interventions, and integration into daily life. This research provides insights useful for future development aiming to improve PWE and CG confidence in using AI technologies for epilepsy care and risk management
Exploration of chronic kidney disease screening, diagnosis and management in Australian general practice using electronic medical record data
No full textBACKGROUND: CKD is a common but under-recognised condition that places significant burden on the individual and the health system globally. Our study applied a set of primary care quality indicators originally developed and validated using Canadian primary care data for screening, diagnosis and monitoring of CKD. These indicators were then applied to a large primary care dataset to assess CKD detection and management practices in Australia. METHODS: We used de-identified data from the Patron repository, which contains data extracted from electronic medical records (EMRs) in Australian general practices. The 16 CKD indicators developed using Canadian EMR data were applied to this dataset. These indicators measured and reported on the use of clinical and pathological tests to diagnose and monitor CKD, the prescribing of antihypertensive and statin medications, and on rates of influenza immunisation. RESULTS: Among the 362,078 unique patients identified across 78 general practices, 24,348 had a diagnosis or pathology consistent with CKD, of whom only 28.1% (6,841) had a diagnosis of CKD recorded. Of the 26,307 patients who initially presented with an eGFR below 60 ml/min/1.73m2, 54.2% (14,254) underwent a repeat eGFR within six months and 28.8% (7,586) completed an ACR test. Of the patients recommended for screening based on the presence of risk factors, 76.1% had an eGFR performed within the last 18 months, whilst 34.2% had an ACR performed in the same period. Rates of monitoring of patients with CKD were slightly higher. A blood pressure had been recorded within the last 9 months in 71.1% of patients with CKD, and in 75.6% of the subset of patients with both diabetes and albuminuria. Around 45% of all patients with CKD were meeting their blood pressure targets at their last recording. CONCLUSIONS: The results of this study demonstrate that it is feasible to derive meaningful and informative indicators of CKD diagnosis and management from primary care EMR data in Australia, which are comparable with international data. The low rates of CKD documentation and pathology monitoring provide opportunities for quality improvement initiatives to reduce disease burden. CLINICAL TRIAL NUMBER: Not applicable
709. Relationship between electroencephalography-based mismatch negativity and antipsychotic treatment response in young people at clinical high risk for psychosis
No full textAbstract
Background
Antipsychotic medications are often used to treat individuals at clinical high risk for psychosis (CHR-P). However, up to 75% of these individuals will not develop psychotic disorders, nor benefit from such treatments. To optimize treatment, it is important to tailor antipsychotic prescriptions based on individual prognostic markers of positive treatment response. We posit that one such marker is mismatch negativity (MMN), which is linked to glutamatergic NMDAR hypofunction—a known abnormality in psychotic disorders.
Aims & Objectives
This study aimed to examine the relationship between mismatch negativity (MMN) response and antipsychotic treatment outcomes in CHR-P participants. Since first-line antipsychotics minimally affect glutamate neurotransmission, it is hypothesized that individuals with reduced baseline MMN might respond less to these medications.
Method
Participants engaged in a roving MMN paradigm prior to commencing or when minimally treated with antipsychotic medications. In these paradigms, participants were required to ignore auditory stimuli while simultaneously performing a tactile distractor task. Average baseline electroencephalographic waveforms and peak MMN amplitudes during the performance of this task were quantified at the Fz electrodes.
Thirty-one participants’ baseline peak MMN amplitudes were correlated against symptomatic changes between the point of commencing antipsychotic treatment and after eight weeks of antipsychotic treatment. Additionally, the relationship between baseline peak MMN amplitudes and longer-term clinical outcomes was also examined by examining group differences in baseline MMN peak amplitudes between patients who (1) had stable CHR-P status, (2) remitted from CHR-P status, or (3) transitioned to a psychotic episode at 12-month study follow-up.
Results
Preliminary analyses indicated that there is no significant relationship between MMN peak amplitudes and antipsychotic treatment outcomes after eight weeks of treatment, nor after twelve months of participation in the study.
Discussion & Conclusions
The null findings obtained in this research may have been impacted upon by limitations in the study design – including small sample sizes in the analyses of short-term antipsychotic response, heterogeneity of the CHR-P population, and the ‘roving’ nature of the MMN paradigm selected. Future analyses should attempt similar analyses with a standard oddball MMN paradigm before making a judgement on the utility of MMN as a biomarker of treatment response
Pulmonary T2* quantification of fetal lung status in congenital diaphragmatic hernia: future alternative to ultrasound?
No full text10.1038/s41390-025-04241-
‘Playing to extinction’: the commercial determinants of gambling-related harm, suicidality and suicide
No full textThis paper presents a model of the commercial determinants of health in the context of gambling-related harm, suicidality and suicide. It outlines the ways the gambling ecosystem undermines suicide prevention efforts by driving harmful engagement with gambling. Using the dominant, orthodox discourse of 'responsible gambling', the ecosystem relies on the effects of addiction to underpin, sustain, and grow its power. Attempts to introduce effective interventions to prevent gambling-related harms are often blocked by the gambling ecosystem actors, using an evidence base that is biased by its focus on individual level causation and the attendant 'responsible gambling' responses. This emphasis on individual responsibility diverts attention from the practices of the industry, generates stigma and shame for those harmed, downplays serious harms caused by gambling, and contributes to the suicide toll. As most gambling activity is unrecorded, and systems for monitoring harms are underdeveloped, the true extent of these consequences have been largely invisible. This makes it more difficult to hold governments to account to regulate and prevent gambling-related harms, including suicidality and suicide. With growing evidence of harms linked to gambling, including suicide and increasing public concern, we present measures that could be adopted to disrupt these determinants and improve accountability to prevent harms and save lives
Demystifying cognitive bias in the diagnostic process for frontline clinicians and educators; new words for old ideas
No full textDiagnostic error is a pervasive problem in healthcare with approximately one-third of adverse events in hospitals attributed to a failure in the diagnostic process. Cognitive biases are systematic, often unconscious, automatic patterns of thought that sometimes skew thinking and are considered a major contributor to diagnostic error. More than 100 different biases have been described that affect clinical decision-making, and the challenge for educators and clinicians is bringing the conceptual knowledge of cognitive bias to the bedside in an applicable and useful way to mitigate the effects of cognitive bias in diagnosis. The language that is commonly used around cognitive bias is technical in nature, often with complicated and nuanced descriptions, so developing a clear understanding of cognitive bias is a task that needs sophisticated language and memory skills as well as clinical reasoning skills. A novel language approach to learning and talking about biases in medicine is to use idioms, short phrases with a particular meaning that differs from the meaning of each word on their own, to simplify the terminology and improve recognition of cognitive bias at the frontline. We present 'The Idiom's Guide to Cognitive Bias', a Table that lists 21 common cognitive biases in the diagnostic process, and defines each, offering a healthcare example and possible explanation for why each occurs. The benefit of The Guide is its practical approach to reinforcing cognitive and medical concepts through the synergy of language and imagery and to demystify cognitive bias in the diagnostic process