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DOAJ Open Access 2026
Bilateral native knee septic arthritis caused by group G Streptococcus: A rare presentation in an uncommon host

Noopur Basu, Matthew Ryan, Joshua Altman

Background: Septic arthritis is an uncommon but severe condition that can lead to rapidly progressive articular destruction and septicemia. Although the knee is the most commonly affected joint in septic arthritis, bilateral involvement is an exceedingly rare condition often associated with immunocompromising conditions, medical comorbidities or other sources of infection. Case report: A 74-year-old male immunocompetent patient presented with two to three days of atraumatic bilateral knee pain and swelling with difficulty ambulating, with presenting vital signs concerning for sepsis. Physical exam was notable for large bilateral knee effusions, warmth and significantly limited range of motion. Bilateral knee arthrocentesis was performed with synovial fluid analysis consistent with bilateral septic arthritis. The patient was managed with intravenous antibiotics and operative arthrotomy and irrigation. Synovial fluid cultures from the emergency department and operating room, as well as 4/4 blood cultures all grew Group G streptococcus. No primary source of infection was identified. The patient completed a course of intravenous antibiotics tailored to culture susceptibility and had resolution of symptoms. Why should an emergency physician be aware of this?: Polyarticular septic arthritis carries high morbidity and mortality. Although uncommon, atypical presentations and absence of usual risk factors can lead to delays or missed diagnoses in the emergency department. It is essential to maintain a high index of suspicion in the patient presenting with undifferentiated multifocal joint pain or swelling, in the appropriate clinical context, to make an early diagnosis and initiate aggressive treatment to prevent complications.

Medical emergencies. Critical care. Intensive care. First aid
DOAJ Open Access 2026
Phalangeal bone growth and implications in Turner syndrome

Min Jae Kang, Min Jae Kang, Roopa Kanakatti Shankar et al.

PurposeSkeletal abnormalities are common in Turner Syndrome (TS), yet data on objective radiographic markers are limited. We aimed to establish normative reference ranges for phalangeal length ratios and assess their utility in detecting skeletal abnormalities in TS.MethodsWe analyzed 4,082 female bone age X-rays (<18 years) from the Radiological Society of North America (RSNA) database after quality screening and outlier exclusion as a reference cohort. Phalangeal length ratios—4th to 3rd metacarpal (4:3 MC), 5th to 3rd metacarpal (5:3 MC), and 5th to 3rd middle phalanx (5:3 MP)—were measured and compared in 81 TS patients seen at a single center. Additional skeletal features such as SHOX deficiency-related signs and brachydactyly type A3 (BDA3) were assessed.ResultsIn reference subjects, 4:3 MC and 5:3 MC ratios remained stable across most age groups, while the 5:3 MP ratio increased with age. TS patients showed a significantly lower 4:3 MC and 5:3 MP ratios (P < 0.001, P = 0.002, respectively) compared to ones from reference subjects. A low 4:3 MC ratio (<–2 SD) was seen in 27.2% of TS patients. The 4:3 MC ratio correlated with height percentile (r = 0.27, P = 0.02). BDA3 was more prevalent in TS compared to reference subjects (13.6% vs. 2.1%, P < 0.001) and associated with low MC ratios.ConclusionNormative reference ranges for phalangeal length ratios were established and differences in 4:3 and 5:3 MP ratios in patients with TS were identified compared to the reference group. Further studies with larger TS cohorts are needed to confirm the clinical utility of these radiographic biomarkers.

Diseases of the endocrine glands. Clinical endocrinology
arXiv Open Access 2025
Towards culturally-appropriate conversational AI for health in the majority world: An exploratory study with citizens and professionals in Latin America

Dorian Peters, Fernanda Espinoza, Marco da Re et al.

There is justifiable interest in leveraging conversational AI (CAI) for health across the majority world, but to be effective, CAI must respond appropriately within culturally and linguistically diverse contexts. Therefore, we need ways to address the fact that current LLMs exclude many lived experiences globally. Various advances are underway which focus on top-down approaches and increasing training data. In this paper, we aim to complement these with a bottom-up locally-grounded approach based on qualitative data collected during participatory workshops in Latin America. Our goal is to construct a rich and human-centred understanding of: a) potential areas of cultural misalignment in digital health; b) regional perspectives on chatbots for health and c)strategies for creating culturally-appropriate CAI; with a focus on the understudied Latin American context. Our findings show that academic boundaries on notions of culture lose meaning at the ground level and technologies will need to engage with a broader framework; one that encapsulates the way economics, politics, geography and local logistics are entangled in cultural experience. To this end, we introduce a framework for 'Pluriversal Conversational AI for Health' which allows for the possibility that more relationality and tolerance, rather than just more data, may be called for.

en cs.HC, cs.AI
arXiv Open Access 2025
Evolution of Extreme Madden-Julian Oscillation Events and their Impacts on South America

Mónica Minjares, Álvaro Corral, Marcelo Barreiro

This study examines the evolution of extreme Madden-Julian Oscillation (MJO) events and their impacts on South America during the austral summer. Furthermore, the study explores how the different ENSO phases modulate extreme MJO events, and how the combined effects impact South American climate. Extreme MJO events are defined as those exceeding a specific threshold based on the events distribution, distinguishing them from weak events. Our analysis shows that extreme MJO events most frequently initiate in phases 2-3 throughout the year, with similar distributions across phases 8-1, 6-7, and 4-5. This distribution is also characteristic of winter, while in summer, initiation is more balanced between phases 2-3 and 8-1. In contrast, weak events predominantly start in phases 4-5 year-round, followed by phases 2-3, with phases 8-1 and 6-7 occurring at similar frequencies. Seasonally, weak event initiation prevails in phases 4-5 during summer, while in winter, it is evenly distributed between phases 8-1 and 4-5. Additionally, during La Niña, extreme events tend to last longer than during El Niño, a pattern not observed in weak events. A composite analysis of outgoing longwave radiation (OLR), eddy streamfunction, and velocity potential was conducted, with particular focus on the initiation phases 2-3 and 6-7 to determine which phases result in the most significant impacts and how the associated anomalies evolve. The findings show that enhanced (suppressed) convection centers in the equatorial region during extreme events are more intense and exhibit a southeastern displacement compared to those during weak events. These extreme MJO events influence the South American rainfall Dipole (SAD), a key feature of regional climate variability and results show that extreme MJO events induce more intense rainfall anomalies of larger spatial extent compared to weak events.

en physics.ao-ph
arXiv Open Access 2025
Identifying the post-pandemic determinants of low performing students in Latin America through Interpretable Machine Learning methods

Marcos Delprato

Introduction. The high prevalence of students not achieving basic learning competencies in Latin America (LAC) is concerning, even more so considering the region's deep structural inequalities and the larger post-pandemic learning losses. Within this scenario, the paper aims to contribute to the identification of the determinants of bottom and low performers (below level 2). Methodology. Based on 2022 data from the Programme for International Student Assessment (PISA) for 10 LAC countries, and using a stacking model integrating binary classification models as well as by applying Shapley Additive Explanations (SHAP) analysis for interpretability, we identify critical factors impacting on the student performance across low performers groups. Results. We find that a student with the highest probability of being a not achiever speaks a minority language and had repeated, has no digital devices at home, comes from a poor family and works for payment half of the week, and the school the student attends has wide disadvantages such as bad school climate, weak Information and Communication Technology (ICT) infrastructure and poor teaching quality (only a third of teachers being certified). For countries' estimates, we find quite homogeneous patterns regarding the contribution of top ranked factors, with repetition at primary, household wealth, and educational ICT inputs being top ten ranked covariates in at least 8 out of the 10 total countries. Discussions. The paper findings contribute to the broad literature on strategies to identify and to target those most left behind in Latin American education systems.

en econ.GN

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