The Use of a Spanish-Translated PrEP Stigma Scale among the Latino Sample of the UNITE Cohort Study.

Pre-Exposure Prophylaxis (PrEP) related stigma is linked to inadequate PrEP uptake, yet there are no validated scales to test this association among Spanish-speaking LSMM. The current study examined if the Spanish-translated PrEP Stigma Scale (PSS) was psychometrically appropriate for implementing in Spanish language dominant Latino/e/x Sexual Minority Men (SMM). Recruitment was conducted using geosocial networking applications, social media sites, and e-mail blasts (N=3,049). First, we utilized Item Response Theory (IRT) modeling to evaluate the reliability of the PSS items and the latent construct across both language groups (nEnglish = 2844 and nSpanish = 205). Subsequently, we applied the PSS scale in a theoretical application by examining its association with key steps in the PrEP uptake cascade (i.e., perceived PrEP candidacy, PrEP willingness, PrEP intentions, and having spoken to provider about PrEP) stratified by language. Results of the IRT analyses provided evidence that the translated version of the PSS was appropriate for use among this sample. Further, among English respondents, PrEP stigma was negatively associated with perceived PrEP candidacy (B=-0.30, p=<.001), PrEP willingness (B=-0.46, p=<.001), and PrEP intentions (B=-0.23, p=.003). PrEP stigma, among Spanish respondents, was not significantly associated with any of the PrEP cascade steps. This study demonstrated that the PSS scale performs adequately for both English and Spanish-speaking Latino SMM. However, researchers and health professionals alike should pay close attention to the nuanced effects in U.S. based English and Spanish language samples as PrEP stigma may impact the PrEP cascade for one language sample and not the other.

Large language model produces high accurate diagnosis of cancer from end-motif profiles of cell-free DNA.

Instruction-tuned large language models (LLMs) demonstrate exceptional ability to align with human intentions. We present an LLM-based model-instruction-tuned LLM for assessment of cancer (iLLMAC)-that can detect cancer using cell-free deoxyribonucleic acid (cfDNA) end-motif profiles. Developed on plasma cfDNA sequencing data from 1135 cancer patients and 1106 controls across three datasets, iLLMAC achieved area under the receiver operating curve (AUROC) of 0.866 [95% confidence interval (CI), 0.773-0.959] for cancer diagnosis and 0.924 (95% CI, 0.841-1.0) for hepatocellular carcinoma (HCC) detection using 16 end-motifs. Performance increased with more motifs, reaching 0.886 (95% CI, 0.794-0.977) and 0.956 (95% CI, 0.89-1.0) for cancer diagnosis and HCC detection, respectively, with 64 end-motifs. On an external-testing set, iLLMAC achieved AUROC of 0.912 (95% CI, 0.849-0.976) for cancer diagnosis and 0.938 (95% CI, 0.885-0.992) for HCC detection with 64 end-motifs, significantly outperforming benchmarked methods. Furthermore, iLLMAC achieved high classification performance on datasets with bisulfite and 5-hydroxymethylcytosine sequencing. Our study highlights the effectiveness of LLM-based instruction-tuning for cfDNA-based cancer detection.

Capturing subjective cognitive decline with a new combined index in low education patients with Parkinson's disease.

Objectives: Subjective Cognitive Decline (SCD) refers to self-reported cognitive decline with normal global cognition. This study aimed to capture SCD among low educated patients with Parkinson's disease (PD) using a newly established indicator. Methods: We recruited 64 PD patients with low education levels (education ≤12 years) for the study. The presence of SCD was determined based on a Unified Parkinson's Disease Rating Scale Part I (1.1) score ≥ 1. Spearman analysis and multivariate binary logistic regression analyses were conducted to investigate factors associated with the PD-SCD group. The receiver operating characteristic (ROC) curve was used to evaluate the sensitivity and specificity of the new combined index. Results: The prevalence of SCD in PD patients was 43.75%. Low educated PD-SCD patients had higher scores on the Non-Motor Symptoms Scale (NMSS), Parkinson's Fatigue Scale (PFS), Epworth Sleepiness Scale (ESS), as well as higher scores on the UPDRS-I and UPDRS-II, compared to PD patients without SCD. They also demonstrated poorer performance on the Montreal Cognitive Assessment (MoCA), particularly in the domains of executive abilities/attention/language. Multivariate binary regression confirmed the significant association between PD-SCD and MoCA-executive abilities/attention/language. Based on these findings, a combined index was established by summing the scores of MoCA-executive abilities, MoCA-attention, and MoCA-language. ROC analysis showed that the combined index could differentiate PD-SCD patients with an area under the curve (AUC) of 0.876. A score of 12 or less on the combined index had a sensitivity of 73.9% and a specificity of 76.2% for diagnosing PD-SCD. Conclusion: These low education patients with PD-SCD may exhibit potential PD-related pathological changes. It is important for clinicians to identify PD-SCD patients as early as possible. The newly combined index can help capture these low educated PD-SCD patients, with an AUC of 0.867, and is expected to assist clinicians in earlier identification and better management of PD patients.

Exploring the role of Large Language Models in haematology: A focused review of applications, benefits and limitations.

Large language models (LLMs) have significantly impacted various fields with their ability to understand and generate human-like text. This study explores the potential benefits and limitations of integrating LLMs, such as ChatGPT, into haematology practices. Utilizing systematic review methodologies, we analysed studies published after 1 December 2022, from databases like PubMed, Web of Science and Scopus, and assessing each for bias with the QUADAS-2 tool. We reviewed 10 studies that applied LLMs in various haematology contexts. These models demonstrated proficiency in specific tasks, such as achieving 76% diagnostic accuracy for haemoglobinopathies. However, the research highlighted inconsistencies in performance and reference accuracy, indicating variability in reliability across different uses. Additionally, the limited scope of these studies and constraints on datasets could potentially limit the generalizability of our findings. The findings suggest that, while LLMs provide notable advantages in enhancing diagnostic processes and educational resources within haematology, their integration into clinical practice requires careful consideration. Before implementing them in haematology, rigorous testing and specific adaptation are essential. This involves validating their accuracy and reliability across different scenarios. Given the field's complexity, it is also critical to continuously monitor these models and adapt them responsively.

Person-based design and evaluation of MIA, a digital medical interview assistant for radiology.

Introduction: Radiologists frequently lack direct patient contact due to time constraints. Digital medical interview assistants aim to facilitate the collection of health information. In this paper, we propose leveraging conversational agents to realize a medical interview assistant to facilitate medical history taking, while at the same time offering patients the opportunity to ask questions on the examination. Methods: MIA, the digital medical interview assistant, was developed using a person-based design approach, involving patient opinions and expert knowledge during the design and development with a specific use case in collecting information before a mammography examination. MIA consists of two modules: the interview module and the question answering module (Q&A). To ensure interoperability with clinical information systems, we use HL7 FHIR to store and exchange the results collected by MIA during the patient interaction. The system was evaluated according to an existing evaluation framework that covers a broad range of aspects related to the technical quality of a conversational agent including usability, but also accessibility and security. Results: Thirty-six patients recruited from two Swiss hospitals (Lindenhof group and Inselspital, Bern) and two patient organizations conducted the usability test. MIA was favorably received by the participants, who particularly noted the clarity of communication. However, there is room for improvement in the perceived quality of the conversation, the information provided, and the protection of privacy. The Q&A module achieved a precision of 0.51, a recall of 0.87 and an F-Score of 0.64 based on 114 questions asked by the participants. Security and accessibility also require improvements. Conclusion: The applied person-based process described in this paper can provide best practices for future development of medical interview assistants. The application of a standardized evaluation framework helped in saving time and ensures comparability of results.

Characterizing Myasthenia Gravis Symptoms, Exacerbations, and Crises From Neurologist's Clinical Notes Using Natural Language Processing.

Background Myasthenia gravis (MG) is a rare, autoantibody neuromuscular disorder characterized by fatigable weakness. Real-world evidence based on administrative and structured datasets regarding MG may miss important details related to the clinical encounter. Examination of free-text clinical progress notes has the potential to illuminate aspects of MG care. Objective The primary objective was to examine and characterize neurologist progress notes in the care of individuals with MG regarding the prevalence of documentation of clinical subtypes, antibody status, symptomatology, and MG deteriorations, including exacerbations and crises. The secondary objectives were to categorize MG deteriorations into practical, objective states as well as examine potential sources of clinical inertia in MG care. Methods We performed a retrospective, cross-sectional analysis of de-identified neurologist clinical notes from 2017 to 2022. A qualitative analysis of physician descriptions of MG deteriorations and a discussion of risks in MG care (risk for adverse effects, risk for clinical decompensation, etc.) was performed. Results Of the 3,085 individuals with MG, clinical subtypes and antibody status identified included gMG (n = 400; 13.0%), ocular MG (n = 253; 8.2%), MG unspecified (2,432; 78.8%), seropositivity for acetylcholine receptor antibody (n = 441; 14.3%), and MuSK antibody (n = 29; 0.9%). The most common gMG manifestations were dysphagia (n = 712; 23.0%), dyspnea (n = 626; 20.3%), and dysarthria (n = 514; 16.7%). In MG crisis patients, documentation of difficulties with MG standard therapies was common (n = 62; 45.2%). The qualitative analysis of MG deterioration types includes symptom fluctuation, symptom worsening with treatment intensification, MG deterioration with rescue therapy, and MG crisis. Qualitative analysis of MG-related risks included the toxicity of new therapies and concern for worsening MG because of changing therapies. Conclusions This study of neurologist progress notes demonstrates the potential for real-world evidence generation in the care of individuals with MG. MG patients suffer fluctuating symptomatology and a spectrum of clinical deteriorations. Adverse effects of MG therapies are common, highlighting the need for effective, less toxic treatments.

Awareness and Knowledge of Congenital Cytomegalovirus (cCMV) Among Audiologists and Speech-Language Pathologists in Saudi Arabia: A Cross Sectional Survey.

Congenital cytomegalovirus (cCMV) is the most prevalent congenital infection in the world. It can result in various neurodevelopmental disorders, one of which is environmental hearing loss among children. This study aimed to assess the awareness and knowledge of cCMV among audiologists and speech-language pathologists (SLPs) in Saudi Arabia and to seek their perception of it. An online survey was conducted from May to June 2023, targeting participants through social media, and a descriptive and inferential analysis was performed. A total of 107 participants (31 audiologists and 76 SLPs) were enrolled in this study. Awareness about cCMV was significantly higher among audiologists (84%) compared to SLPs (49%) (p-value < 0.001). However, both groups exhibited poor cCMV knowledge, which was revealed by their low mean knowledge scores (6.8/14 for audiologists and 5.7/14 for SLPs). The difference between their mean scores was non-significant (p-value > 0.05). The majority of SLPs and audiologists agreed that it is crucial for them to learn more about cCMV to enrich their professional backgrounds. This study emphasized the necessity for cCMV education for audiologists and SLPs. Increased awareness and knowledge may allow them to be more mindful of cCMV symptoms and therefore provide enhanced service to their pediatric patients.

GBERT: A hybrid deep learning model based on GPT-BERT for fake news detection.

The digital era has expanded social exposure with easy internet access for mobile users, allowing for global communication. Now, people can get to know what is going on around the globe with just a click; however, this has also resulted in the issue of fake news. Fake news is content that pretends to be true but is actually false and is disseminated to defraud. Fake news poses a threat to harmony, politics, the economy, and public opinion. As a result, bogus news detection has become an emerging research domain to identify a given piece of text as genuine or fraudulent. In this paper, a new framework called Generative Bidirectional Encoder Representations from Transformers (GBERT) is proposed that leverages a combination of Generative pre-trained transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) and addresses the fake news classification problem. This framework combines the best features of both cutting-edge techniques-BERT's deep contextual understanding and the generative capabilities of GPT-to create a comprehensive representation of a given text. Both GPT and BERT are fine-tuned on two real-world benchmark corpora and have attained 95.30 % accuracy, 95.13 % precision, 97.35 % sensitivity, and a 96.23 % F1 score. The statistical test results indicate the effectiveness of the fine-tuned framework for fake news detection and suggest that it can be a promising approach for eradicating this global issue of fake news in the digital landscape.

Digital health tools in nephrology: A comparative analysis of AI and professional opinions via online polls.

Background: Professional opinion polling has become a popular means of seeking advice for complex nephrology questions in the #AskRenal community on X. ChatGPT is a large language model with remarkable problem-solving capabilities, but its ability to provide solutions for real-world clinical scenarios remains unproven. This study seeks to evaluate how closely ChatGPT's responses align with current prevailing medical opinions in nephrology. Methods: Nephrology polls from X were submitted to ChatGPT-4, which generated answers without prior knowledge of the poll outcomes. Its responses were compared to the poll results (inter-rater) and a second set of responses given after a one-week interval (intra-rater) using Cohen's kappa statistic (κ). Subgroup analysis was performed based on question subject matter. Results: Our analysis comprised two rounds of testing ChatGPT on 271 nephrology-related questions. In the first round, ChatGPT's responses agreed with poll results for 163 of the 271 questions (60.2%; κ = 0.42, 95% CI: 0.38-0.46). In the second round, conducted to assess reproducibility, agreement improved slightly to 171 out of 271 questions (63.1%; κ = 0.46, 95% CI: 0.42-0.50). Comparison of ChatGPT's responses between the two rounds demonstrated high internal consistency, with agreement in 245 out of 271 responses (90.4%; κ = 0.86, 95% CI: 0.82-0.90). Subgroup analysis revealed stronger performance in the combined areas of homeostasis, nephrolithiasis, and pharmacology (κ = 0.53, 95% CI: 0.47-0.59 in both rounds), compared to other nephrology subfields. Conclusion: ChatGPT-4 demonstrates modest capability in replicating prevailing professional opinion in nephrology polls overall, with varying performance levels between question topics and excellent internal consistency. This study provides insights into the potential and limitations of using ChatGPT in medical decision making.

Embracing virtual reality in rehabilitation of post-stroke aphasia.

About one-third of stroke survivors experience aphasia, i.e., language dysfunction caused by brain damage. Aphasia affects not only a person's ability to communicate, but it often leads to the inability to return to work, loss of close relationships, diminished quality of life, negative self-perception, and depression. Yet persons with aphasia are globally underserved due to limited access to resources, which limits their chance for recovery. Immersive virtual reality (VR) has the potential to solve this problem and deliver efficient, personalized treatments to millions of people worldwide who need access to rehabilitation services or more flexibility in treatment delivery. To reduce the global burden of stroke experts recommend taking bold, pragmatic actions across all four pillars of stroke quadrangle-surveillance, prevention, acute care, and rehabilitation. Embracing immersive VR-based rehabilitation of poststroke aphasia would be one step in that direction.

Word learning by children with developmental language disorder: Identifying gaps in our understanding of spaced retrieval effects.

Background and aims: Current evidence shows that children with developmental language disorder (DLD) benefit from spaced retrieval during word learning activities. Word recall is quite good relative to recall with alternative word learning procedures. However, recall on an absolute basis can be improved further; many studies report that fewer than two-thirds of the words are learned, even with the assistance of spaced retrieval during the learning activities. In this article we identify details of spaced retrieval that are less well understood in an effort to promote more effective learning through retrieval practice. Main contribution: We discuss the importance of factors such as: (a) integrating immediate retrieval with spaced retrieval trials; (b) determining whether gradual increases in spacing have more than short-term benefits relative to equal spacing; (c) discovering the number of successful retrievals sufficient to ensure later recall; (d) using spaced retrieval to avoid erosion of phonetic details on later recall tests; and (e) whether the well-documented difficulties with learning word forms might be tied to a particular subgroup of children with DLD. We also speculate on some of the possible reasons why spaced retrieval is beneficial in the first place. Conclusions: Although many children with DLD make gains in word learning through procedures that incorporate spaced retrieval, there are numerous details involved in the process that can alter its success. Until we have a better understanding of the boundaries of spaced retrieval's effectiveness, we will not be taking full advantage of this promising addition to word learning procedures. Implications: Spaced retrieval activities can be an important addition to the resources that clinicians and educators have available to assist children in their word learning. With a deeper understanding of the issues discussed here, we should be able to put spaced retrieval to even greater use.

Is language impaired in Spanish-speaking children with autism spectrum disorder level 1?

The current diagnostic criteria for the autism spectrum disorder (ASD) include the possibility to specify concomitant language difficulties. Purpose: Our main aim was to explore whether children with ASD-Level 1 (ASD-L1) present difficulties in the acquisition of structural language, as little work has been done in this regard so far. As a secondary aim we evaluated the degree to which the potential language impairment in ASD is directly associated with their social communication deficits or it represents a distinct deficit. Methods: To further clarify the nature and characteristics of putative language difficulties in ASD-L1, we evaluated language skills in 89 children and preadolescents diagnosed with ASD-L1, and a group of typically developing participants (TD). All of them were between 8 and 13 years old and had similar socioeconomic backgrounds. Results: Children with ASD-L1 obtained lower scores than those in TD group in repeating sentences, in finding the semantic relationships between words, and in applying word structure rules (morphology). Congruently, the core language standard score was lower in the ASD-L1 group, and the proportion of language delay was significantly higher in the ASD-L1 group than in the control group. Conclusion: Language scores were associated with autistic traits; thus, language performance in ASD-L1 is closely related to autistic symptoms. These results are discussed according to the literature on linguistic deficits in ASD-L1 and their relations with phonological working memory.

How do children with language disorder perceive their peer interactions? A qualitative investigation.

Background and aims: Peer interaction difficulties are often elevated amongst children with language disorders, yet the mechanisms underlying these difficulties are unclear. Previous research indicates that poor conflict management, social withdrawal, emotion regulation difficulties, and reduced prosocial behavior may contribute to peer interaction difficulties. However, this research often uses adult perspectives, failing to acknowledge child perceptions of these experiences. The present study aimed to qualitatively investigate perceptions of peer interactions from the perspective of children with language disorders. Methods: Seven participants aged between 7- and 10-years-old took part. All participants were diagnosed with a language disorder and had language as their primary area of difficulty. Participants were recruited from a specialist language school and via an online database. Semi-structured interviews were conducted, with participants given the choice to answer questions verbally or creatively, using toys or drawing materials. Interview transcripts were analyzed using interpretative phenomenological analysis. Results: Participants valued play, conversation, and helping others. They felt that spending time with peers could alleviate loneliness. However, sometimes solitude was needed as social interaction could be overwhelming. Participants found conflict challenging and exhibited difficulties with regulating emotions. Participants relied on running away, retaliation, or asking an adult for help, to resolve conflict. Conclusions and implications: The findings suggest that children with language disorders are socially motivated and have relative strengths in displaying prosocial behavior. However, children with language disorders require support to promote positive relationships. This support includes help with making deeper connections with peers, opportunities to spend time alone when needed, and providing adept conflict resolution and emotion regulation strategies.

Toward mastering foreign-language translations: transfer between productive and receptive learning.

Learners can study foreign language-English vocabulary (e.g., denken - to think) both receptively and productively. Receptive learning involves being cued with a foreign language word (e.g., denken) and trying to translate it (i.e., to think). Productive learning involves being cued with an English word (e.g., to think) and trying to produce the translation. When students use retrieval practice to learn foreign-language translations in one direction (e.g., receptively) until they correctly recall the translation, do they demonstrate transfer in the other direction (i.e., productively)? Across three experiments, we answered this question by manipulating the order of learning schedule (reception first followed by production or vice versa). For a given schedule, participants continued to practice retrieving translations (with feedback) using the dropout method until they correctly recalled each translation three times; they then proceeded to practice the pairs in the opposite direction until they correctly recalled each translation three times. Across all experiments, transfer was partial (learning in one direction did not entirely eliminate the need to practice in the other), but transfer did occur regardless of which schedule students used first during practice.

Improving viral annotation with artificial intelligence.

Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their dependence on hosts for replication positions phages as unique sensors of ecosystem features and environmental pressures. High-throughput sequencing approaches have begun to give us access to the diversity and range of phage populations in complex microbial community samples, and metagenomics is currently the primary tool with which we study phage populations. The study of phages by metagenomic sequencing, however, is fundamentally limited by viral diversity, which results in the vast majority of viral genomes and metagenome-annotated genomes lacking annotation. To harness bacteriophages for applications in human and environmental health and disease, we need new methods to organize and annotate viral sequence diversity. We recently demonstrated that methods that leverage self-supervised representation learning can supplement statistical sequence representations for remote viral protein homology detection in the ocean virome and propose that consideration of the functional content of viral sequences allows for the identification of similarity in otherwise sequence-diverse viruses and viral-like elements for biological discovery. In this review, we describe the potential and pitfalls of large language models for viral annotation. We describe the need for new approaches to annotate viral sequences in metagenomes, the fundamentals of what protein language models are and how one can use them for sequence annotation, the strengths and weaknesses of these models, and future directions toward developing better models for viral annotation more broadly.

Speech sound development of young Dutch children with a developmental language disorder: A complex matter.

BACKGROUND: Approximately 50% of all young children with a developmental language disorder (DLD) also have problems with speech production. Research on speech sound development and clinical diagnostics of speech production difficulties focuses mostly on accuracy; it relates children's phonological realizations to adult models. Contrarily to these relational analyses, independent analyses indicate the sounds and structures children produce irrespective of accuracy. Such analyses are likely to provide more insight into a child's phonological strengths and limitations, and may thus provide better leads for treatment. AIMS: Ram (1) To contribute to a more comprehensive overview of the speech sound development of young Dutch children with DLD by including independent and relational analyses, (2) to develop an independent measure to assess these children's speech production capacities; and (3) to examine the relation between independent and relational speech production measures for children with DLD. METHODS & PROCEDURES: We describe the syllable structures and sounds of words elicited in two picture-naming tasks of 82 children with DLD and speech production difficulties between ages 2;7 and 6;8. The children were divided into four age groups to examine developmental patterns in a cross-sectional manner. Overviews of the children's productions on both independent and relational measures are provided. We conducted a Spearman correlation analysis to examine the relation between accuracy and independent measures. OUTCOMES & RESULTS: The overviews show these children are able to produce a greater variety of syllable structures and consonants irrespective of target positions than they can produce correctly in targets. This is especially true for children below the age of 4;5. The data indicate that children with DLD have difficulty with the production of clusters, fricatives, liquids and the velar nasal (/ŋ/). Based on existing literature and our results, we designed a Dutch version of an independent measure of word complexity, originally designed for English (word complexity measure-WCM) in which word productions receive points for specific word, syllable and sound characteristics, irrespective of accuracy. We found a strong positive correlation between accuracy scores and scores on this independent measure. CONCLUSIONS & IMPLICATIONS: The results indicate that the use of independent measures, including the proposed WCM, complement traditional relational measures by indicating which sounds and syllable structures a child can produce (irrespective of correctness). Therefore, the proposed measure can be used to monitor the speech sound development of children with DLD and to better identify treatment goals, in combination with existing relational measures. WHAT THIS PAPER ADDS: What is already known on the subject Speech production skills can be assessed in different ways: (1) using analyses indicating the structures and sounds a child produces irrespective of accuracy, that is, performance analyses; and (2) using analyses indicating how the productions of a child relate to the adult targets, that is, accuracy analyses. In scientific research as well as in clinical practice the focus is most often on accuracy analyses. As a consequence, we do not know if children who do not improve in accuracy scores, improve in other phonological aspects that are not captured in these analyses, but can be captured by performance analyses. What this study adds to the existing knowledge The overviews show these children are able to produce a greater variety of syllable structures and consonants irrespective of target positions than they can produce correctly in targets. Consequently, adding performance analyses to existing accuracy analyses provides a more complete picture of a child's speech sound development. What are the potential or actual clinical implications of this work? We propose a Dutch version of a WCM, originally designed for English, in which word productions receive points for word structures, syllable structures and sounds, irrespective of accuracy. This measure may be used by Dutch clinicians to monitor the speech sound development of children with DLD and to formulate better treatment goals, in addition to accuracy measures that are already used.

Beyond the here and now: hunter-gatherer socio-spatial complexity and the evolution of language.

Human evolutionary ecology stands to benefit by integrating theory and methods developed in movement ecology, and in turn, to make contributions to the broader field of movement ecology by leveraging our species' distinct attributes. In this paper, we review data and evolutionary models suggesting that major changes in socio-spatial behaviour accompanied the evolution of language. To illustrate and explore these issues, we present a comparison of GPS measures of the socio-spatial behaviour of Hadza hunter-gatherers of northern Tanzania to those of olive baboons (Papio anubis), a comparatively small-brained primate that is also savanna-adapted. While standard spatial metrics show modest differences, measures of spatial diversity, landscape exploration and spatiotemporal displacement between individuals differ markedly. Groups of Hadza foragers rapidly accumulate a vast, diverse knowledge pool about places and things over the horizon, contrasting with the baboon's narrower and more homogeneous pool of ecological information. The larger and more complex socio-spatial world illustrated by the Hadza is one where heightened cognitive abilities for spatial and episodic memory, navigation, perspective taking and communication about things beyond the here and now all have clear value.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Microcalcifications in benign breast biopsies: association with lesion type and risk.

PURPOSE: To characterize associations of microcalcifications (calcs) with benign breast disease lesion subtypes and assess whether tissue calcs affect risks of ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC). METHODS: We analyzed detailed histopathologic data for 4,819 BBD biopsies from a single institution cohort (2002-2013) followed for DCIS or IBC for a median of 7.4 years for cases (N = 338) and 11.2 years for controls. Natural language processing was used to identify biopsies containing calcs based on pathology reports. Univariable and multivariable regression models were applied to assess associations with BBD lesion type and age-adjusted Cox proportional hazard regressions were performed to model risk of IBC or DCIS stratified by the presence or absence of calcs. RESULTS: Calcs were identified in 2063 (42.8%) biopsies. Calcs were associated with older age at BBD diagnosis (56.2 versus 49.0 years; P < 0.001). Overall, the risk of developing IBC or DCIS did not differ significantly between patients with calcs (HR 1.13, 95% CI 0.90, 1.41) as compared to patients without calcs. Stratification by BBD severity or subtype, age at BBD biopsy, outcomes of IBC versus DCIS, and mammography technique (screen-film versus full-field digital mammography) did not significantly alter association between calcs and risk. CONCLUSION: Our analysis of calcs in BBD biopsies did not find a significant association between calcs and risk of breast cancer.

An audit of perioperative speech pathology intervention on improving enhanced recovery after surgery in oesophagectomy patients.

PURPOSE: To evaluate the impact of a speech-language pathology (SLP) pathway on recovery following oesophagectomy. METHOD: An audit was conducted at a single metropolitan public hospital in Sydney, Australia. Patients between 2014-2021 undergoing a three-stage oesophagectomy (n = 41) were included in the study. The sample was divided into two groups, those who received usual care (2014-2019) and those who received perioperative SLP assessment and intervention (2020-2021), with data collected across swallowing and health outcomes. Patient demographics and outcomes between the two groups were compared. RESULT: Patients who received perioperative SLP intervention commenced oral intake faster postoperatively (SLP intervention group Mdn = 6.50 days, IQR = 6.00-7.00; usual care group Mdn = 9.00 days, IQR = 7.00-13.25; p = 0.001). There was no statistically significant difference between groups in rates of aspiration on the postoperative leak test (p = 0.32). No statistically significant differences were found between the two groups in length of hospital stay or number of swallowing-related medical images completed during their admission. CONCLUSION: Perioperative SLP intervention has a positive impact on commencing oral intake following a three-stage oesophagectomy, however, it does not have a significant impact on rates of aspiration postoperatively. This pathway may contribute to enhanced recovery after oesophagectomy.