Notes

miR-152-mediated MKK7 downregulation is actually attenuated through MYCNOS throughout ovarian adenocarcinoma.
Sepsis is common in cirrhosis and is often a result of immune dysregulation. Specific stimuli and pathways of inter-cellular communications between immune cells in cirrhosis and sepsis are incompletely understood. Immune cell-derived extracellular vesicles (EV) were studied to understand mechanisms of sepsis in cirrhosis.

Immune cell-derived EV were measured in cirrhosis patients [Child-Turcotte-Pugh (Child) score A, n=15; B n=16; C n=43 and Child-C with sepsis (n=38)], and healthy controls (HC, n=11). In vitro and in vivo functional relevance of EV in cirrhosis and associated sepsis was investigated.

Monocyte, neutrophil and hematopoietic stem cells associated EV progressively increased with higher Child score (P<.001)and correlated with liver disease severity indices (r
>0.3, P<.001), which further increased in Child C sepsis than without sepsis(P<.001); monocyte EV showing the highest association with disease stage [P=.013; Odds ratio-4.14(1.34-12.42)]. A threshold level of monocyte EV early stratification of sicker patients.
To create a personalised machine learning model for prediction of severe adverse neonatal outcomes (SANO) during the second stage of labour.

Retrospective Electronic-Medical-Record (EMR) -based study.

A cohort of 73868 singleton, term deliveries that reached the second stage of labour, including 1346 (1.8%) deliveries with SANO.

A gradient boosting model was created, analysing 21 million data points from antepartum features (e.g. gravidity and parity) gathered at admission to the delivery unit, and intrapartum data (e.g. cervical dilatation and effacement) gathered during the first stage of labour. Afimoxifene Deliveries were allocated to high-risk and low-risk groups based on the Youden index to maximise sensitivity and specificity.

SANO was defined as either umbilical cord pH levels ≤7.1 or 1-minute or 5-minute Apgar score ≤7.

The model for prediction of SANO yielded an area under the receiver operating curve (AUC) of 0.761 (95% CI 0.748-0.774). A third of the cohort (33.5%, n=24721) were allocated to a high-risk group for SANO, which captured up to 72.1% of these cases (odds ratio 5.3, 95% CI 4.7-6.0; high-risk versus low-risk groups).

Data acquired throughout the first stage of labour can be used to predict SANO during the second stage of labour using a machine learning model. Stratifying parturients at the beginning of the second stage of labour in a 'time out' session, can direct a personalised approach to management of this challenging aspect of labour, as well as improve allocation of staff and resources.

Personalised prediction score for severe adverse neonatal outcomes in labour using machine learning model.
Personalised prediction score for severe adverse neonatal outcomes in labour using machine learning model.Staphylococcus aureus is a common organism in orthopedic infections, but little is known about the genetic diversity of strains during an infectious process. Using periprosthetic joint infection (PJI) as a model, a prospective study was designed to quantify genetic variation among S. aureus strains both among and within patients. Whole genome sequencing and multilocus sequence typing was performed to genotype these two populations at high resolution. In nasal cultures, 78% of strains were of clonal complexes CC5, CC8, and CC30. In PJI cultures, only 63% could be classified in these common clonal complexes. The PJI cultures had a larger proportion of atypical strains, and these atypical strains were associated with poor host status and compromised immune conditions. Mutations in genes involved in fibronectin binding (ebh, fnbA, clfA, and clfB) systematically distinguished later PJI isolates from the first PJI isolate from each patient. Repeated mutations in S. aureus genes associated with extracellular matrix binding were identified, suggesting adaptive, parallel evolution of S. aureus during the development of PJI.Parallel evolution is considered strong evidence for natural selection. However, few studies have investigated the process of parallel selection as it plays out in real time. The common approach is to study historical signatures of selection in populations already well adapted to different environments. Here, to document selection under natural conditions, we study six populations of threespine stickleback (Gasterosteus aculeatus) inhabiting bar-built estuaries that undergo seasonal cycles of environmental changes. Estuaries are periodically isolated from the ocean due to sandbar formation during dry summer months, with concurrent environmental shifts that resemble the long-term changes associated with postglacial colonization of freshwater habitats by marine populations. We used pooled whole-genome sequencing to track seasonal allele frequency changes in six of these populations and search for signatures of natural selection. We found consistent changes in allele frequency across estuaries, suggesting a potential role for parallel selection. Functional enrichment among candidate genes included transmembrane ion transport and calcium binding, which are important for osmoregulation and ion balance. The genomic changes that occur in threespine stickleback from bar-built estuaries could provide a glimpse into the early stages of adaptation that have occurred in many historical marine to freshwater transitions.
Brief interventions (BIs) in primary health care (PHC) settings can be effective in addressing behavioural risk factors of chronic conditions. However, the impact of the characteristics of BI training programs on the uptake of the program and implementation of BIs in Indigenous PHC settings is not fully understood. The B.strong Program was an Indigenous health worker BI training program delivered in Queensland from 2017 to 2020. This study examines the impact of the characteristics of the B.strong Program on its uptake and implementation in PHC settings.

Semi-structured interviews were conducted in 2019 and 2020 with 20 B.strong Program trainees and four health service managers from eight purposively sampled Queensland PHC services, and one Queensland Department of Health manager, to collect their perceptions of the implementation of the B.strong Program. The Consolidated Framework for Implementation Research guided data collection.

Key program characteristics that facilitated both the program uptake and the implementation of BIs were ensuring the cultural appropriateness of the program from development, to engagement with health services and through to delivery, the applicability of the program to trainees' daily clinical work, program credibility, and its ease of access and availability.
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