Conectar
by Danai Sangthong, Pradit Sangthong, Warin Rangubpit, Prapasiri Pongprayoon, Eukote Suwan, Kannika Wongpanit, Wissanuwat Chimnoi, Pacharathon Simking, Sinsamut Sae Ngow, Serge Morand, Roger W. Stich, Sathaporn Jittapalapong
Phylogenetic and population genetic analyses were conducted on tick specimens collected from cattle in northern, northeastern, central, and southern regions of Thailand. Morphological identification indicated these ticks consisted of three species, Rhipicephalus microplus from all four regions, R. sanguineus from the northern and northeastern regions, and a Haemaphysalis species only collected from the northeastern region. Analysis of cytochrome c oxidase subunit I gene (COI) sequences identified R. microplus clades A and C, while clade B was not detected in this study. The same analysis indicated specimens morphologically identified as Haemaphysalis were H. bispinosa, confirming previous reports of their prevalence in northeastern Thailand. H. bispinosa showed low haplotype and nucleotide diversity, suggesting either a bottleneck or founder effect. Both R. microplus clades displayed high haplotype diversity and low nucleotide diversity, a pattern associated with population expansion. Genetic structural analysis revealed significant genetic differences in R. microplus clade A, especially between mainland (northern, northeastern, and central regions) and peninsular (southern region) populations, which indicated limited gene flow between these areas while suggesting movement of these ticks across the mainland. The sequence analyses described in this report enhance understanding of the natural history of ticks in Thailand and are expected to guide and strengthen tick control strategies across Southeast Asia.by Kazuya Takahashi, Michalina Lubiatowska, Huma Shehwana, James K. Ruffle, John A. Williams, Animesh Acharjee, Shuji Terai, Georgios V. Gkoutos, Humayoon Satti, Qasim Aziz
BackgroundThe exact mechanisms underlying paediatric abdominal pain (AP) remain unclear due to patient heterogeneity. This preliminary study aimed to identify AP phenotypes and develop predictive models to explore associated factors, with the goal of guiding future research.
MethodsIn 13,790 children from a large birth cohort, data on paediatric and maternal demographics and comorbidities were extracted from general practitioner records. Machine learning (ML) clustering was used to identify distinct AP phenotypes, and an ML-based predictive model was developed using demographics and clinical features.
Results1,274 children experienced AP (9.2%) (average age: 8.4 ± 1.1 years, male/female: 615/659), who clustered into three distinct phenotypes: Phenotype 1 with an allergic predisposition (n = 137), Phenotype 2 with maternal comorbidities (n = 676), and Phenotype 3 with minimal other comorbidities (n = 340). As the number of allergic diseases or maternal comorbidities increased, so did the frequency of AP, with 17.6% of children with ≥ 3 allergic diseases and 25.6% of children with ≥ 3 maternal comorbidities. The predictive model demonstrated moderate performance in predicting paediatric AP (AUC 0.67), showing that a child’s ethnicity, paediatric allergic diseases, and maternal comorbidities were key predictive factors. When stratified by ML-predicted probability, observed AP rates were 18.9% in the 60% group.
ConclusionsThis study identified distinct AP phenotypes and key risk factors using ML. Furthermore, the predictive ML model enabled risk stratification for paediatric AP. These analyses provide valuable insights to guide future investigations into the mechanisms of AP and may facilitate research aimed at identifying targeted interventions to improve patient outcomes.
Despite increasing proportions of underrepresented minority (URM) medical school graduates, their progression into surgical training and leadership remains disproportionately low. Barriers such as financial constraints, limited mentorship and implicit bias contribute to this disparity, creating a disconnect between the diversity of patient populations and those providing care. While interventions such as mentorship programmes and pipeline initiatives have been implemented, their overall effectiveness has not been systematically evaluated. The primary aim of this scoping review is to map the current landscape of interventions, programmes and policies designed to enhance access to surgical careers for URM learners.
Searches will be conducted on EMBASE, Web of Science and OVID MEDLINE. Three independent reviewers will screen references, extract data and perform analyses with disagreements adjudicated by a fourth reviewer. This review will include studies conducted across all levels of training: secondary (high school or secondary school), postsecondary (undergraduate, medical school) and postgraduate (residency, fellowship), with no geographical restrictions. The definition of URM will be accepted as reported within each individual study, allowing for variability in racial, ethnic, gender, socioeconomic or other criteria. The review will include any structured interventions, programmes or policies aimed at increasing URM representation in surgical education. Data on the nature, duration and target population of each intervention will be extracted. The primary outcome will be the reported impact of interventions on URM representation or participation in surgical education. Secondary outcomes will include characteristics of the study participants, definitions of URM status and any qualitative or quantitative evaluations of intervention effectiveness.
Research ethics approval is not required under University of Toronto policy. Study results will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. Results will be disseminated to relevant stakeholders at conference presentation(s) and submitted for publication in a peer-reviewed journal.
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