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Background: The teaching of reading or reading instruction has largely been carried out in terms of well-developed pedagogies in the field. These pedagogical approaches are, however, derived from research and development in a broad international context, and are often adopted by and implemented in various country settings. Given the contextual variation and resource disparities in South Africa, we feel such settings where approaches are adopted and used to represent a 'one size fits all' approach can be less than ideal. Aim: To explore scientific approaches to reading instruction as alternative approaches that are context specific. Setting: This article questions reading instruction as prescribed in the National Curriculum of South Africa. Methods: A conceptual review of literature was conducted to distil and propose alternatives to the dominant discourses for reading instruction. Results: Given the resource disparities and contextual variations, we argue for and propose a structured approach to reading instruction. Conclusion: Such an alternative should consider scientific evidence, and the teaching of reading needs to be explicit and systematic as well as contextually relevant. We believe it holds promise for improvement in literacy rates as it provides flexible and adaptable approaches. Contribution: We advocate for an alternative approach to reading instruction that is grounded in scientific evidence and emphasises explicit, systematic, and contextually relevant instruction.

Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy information, this study generated a custom interactive and intelligent chatbot (Anatbuddy) through an Open AI Application Programming Interface (API) that enables seamless AI-driven interactions within a secured cloud infrastructure. Anatbuddy was programmed through a Retrieval Augmented Generation (RAG) method to provide context-aware responses to user queries based on a predetermined knowledge base. To compare their outputs, various queries (i.e., prompts) on thoracic anatomy (n = 18) were fed into Anatbuddy and ChatGPT 3.5. A panel comprising three experienced anatomists evaluated both tools' responses for factual accuracy, relevance, completeness, coherence, and fluency on a 5-point Likert scale. These ratings were reviewed by a third party blinded to the study, who revised and finalized scores as needed. Anatbuddy's factual accuracy (mean ± SD = 4.78/5.00 ± 0.43; median = 5.00) was rated significantly higher (U = 84, p = 0.01) than ChatGPT's accuracy (4.11 ± 0.83; median = 4.00). No statistically significant differences were detected between the chatbots for the other variables. Given ChatGPT's current content knowledge limitations, we strongly recommend the anatomy profession develop a custom AI chatbot for anatomy education utilizing a carefully curated knowledge base to ensure accuracy. Further research is needed to determine students' acceptance of custom chatbots for anatomy education and their influence on learning experiences and outcomes.

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22-1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms.

Abstract: Misophonia is characterized by strong negative reactions to everyday sounds, such as chewing, slurping or breathing, that can have negative consequences for daily life. Here, we investigated the role of visual stimuli in modulating misophonic reactions. We recruited 26 misophonics and 31 healthy controls and presented them with 26 sound-swapped videos: 13 trigger sounds paired with the 13 Original Video Sources (OVS) and with 13 Positive Attributable Visual Sources (PAVS). Our results show that PAVS stimuli significantly increase the pleasantness and reduce the intensity of bodily sensations associated with trigger sounds in both the misophonia and control groups. Importantly, people with misophonia experienced a larger reduction of bodily sensations compared to the control participants. An analysis of self-reported bodily sensation descriptions revealed that PAVS-paired sounds led participants to use significantly fewer words pertaining to body parts compared to the OVS-paired sounds. We also found that participants who scored higher on the Duke Misophonia Questionnaire (DMQ) symptom severity scale had higher auditory imagery scores, yet visual imagery was not associated with the DMQ. Overall, our results show that the negative impact of misophonic trigger sounds can be attenuated by presenting them alongside PAVSs.

OBJECTIVE: Paraoxonase-1 (PON1) is a high-density lipoprotein (HDL)-associated enzyme, that has been implicated as a biomarker of cardiovascular risk in patients with rheumatoid arthritis (RA). We aimed to investigate how different biologic therapies affect levels of PON1 and oxylipins. METHODS: 1213 adult patients with RA in the Comparative Effectiveness Registry to study Therapies for Arthritis and Inflammatory CoNditions cohort study with moderate-to-high disease activity (Clinical Disease Activity Index (CDAI) >10) who initiated a new biologic (tocilizumab (TCZ), n=296; abatacept, n=374; tumour necrosis factor inhibitors, n=427; rituximab, n=116) were followed prospectively with serum specimens analysed for PON1 activity by arylesterase (ARYL), lactonase (LAC) and PON assays at baseline and after 6 months of biologic therapy. A targeted panel of oxylipins was evaluated by liquid chromatography-mass spectrometry/mass spectrometry in a subset of patients with the lowest and highest 6-month Disease Activity Score 28 (DAS28)-C reactive protein (CRP) responses in each treatment group. RESULTS: PON1 activity generally increased in the entire cohort after 6 months of new biologic therapy, showing the greatest, most consistent increases in the TCZ group. Increases in all three PON1 domains associated with significant decreases in disease activity in DAS28-CRP/CDAI (p

Social disconnection, including objective social isolation and subjective loneliness, is linked to substantial health risks. Yet, little is known about the predictors of social disconnection in individuals with mental illness. Here, we used machine learning to identify predictors of social isolation and loneliness in schizophrenia (N = 72), a psychiatric condition associated with social disconnection. For comparison, we also included two other groups: a psychiatric comparison sample of bipolar disorder (N = 48) and a community sample enriched for social isolation (N = 151). We fitted statistical models of social isolation and loneliness within and across groups. Each model included five candidate predictors: social avoidance motivation, depression, nonsocial cognition, social anhedonia, and social cognition. The results showed that social anhedonia explained unique variance in social isolation and loneliness in all samples, suggesting that it contributes to social isolation and loneliness broadly. However, nonsocial cognition explained unique variance in social isolation only within schizophrenia. Thus, social anhedonia could be a potential intervention target across populations, whereas nonsocial cognition may play a unique role in determining social disconnection in schizophrenia.

PurposePrevious studies have demonstrated that radiologists and other providers perceive maging to be higher than they actually are. Thus, pregnant patients were less likely to receive ionizing radiation procedures. While it is imperative to minimize fetal radiation exposure, clinicians must remember that diagnostic studies should not be avoided due to fear of radiation, particularly if the imaging study can significantly impact patient care. Although guidelines do exist regarding how best to image pregnant patients, many providers are unaware of these guidelines and thus lack confidence when making imaging decisions for pregnant patients. This study aimed to gather information about current education, confidence in, and knowledge about emergency imaging of pregnant women among radiology, emergency medicine, and OB/GYN providers.MethodsWe created and distributed an anonymous survey to radiology, emergency medicine, and OB/GYN providers to evaluate their knowledge and confidence in imaging pregnant patients in the emergent setting. This study included a questionnaire with the intent of knowing the correct answers among physicians primarily across the United States (along with some international participation). We conducted subgroup analyses, comparing variables by specialty, radiology subspecialty, and training levels. Based on the survey results, we subsequently developed educational training videos.Results108 radiologists, of which 32 self-identified as emergency radiologists, ten emergency medicine providers and six OB/GYN clinicians completed the survey. The overall correct response rate was 68.5%, though performance across questions was highly variable. Within our 18-question survey, four questions had a correct response rate under 50%, while five questions had correct response rates over 90%. Most responding physicians identified themselves as either "fairly" (58/124, 47%) or "very" (51/124, 41%) confident. Amongst specialties, there were differences in performance concerning the knowledge assessment (p = 0.049), with the strongest performance from radiologists. There were no differences in knowledge by training level (p = 0.4), though confidence levels differed significantly between attending physicians and trainees (p