Modelling Interventions to Combat Antibacterial Resistance in East Africa Using Causal Bayesian Networks.

Antibacterial resistance (ABR) poses significant challenges to combating infections worldwide. ABR drivers are interconnected, complicating identification of intervention points. Researchers need a systems-based perspective that considers interrelated drivers collectively.

Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa: a call for action.

Background: In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR.

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance: A study of urinary tract infection patients in Kenya, Tanzania and Uganda.

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviour, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers.

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance: A study of urinary tract infection patients in Kenya, Tanzania and Uganda.

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviours, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers.

Treatment of missing data in Bayesian network structure learning: an application to linked biomedical and social survey data.

Background: Availability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based analyses. Among these, Bayesian networks have great potential to tackle complex interdisciplinary problems, because they can easily model inter-relations between variables. They work by encoding conditional independence relationships discovered via advanced inference algorithms.

The stigma of patients with chronic insomnia: a clinical study.

Background: The objective of this study was to explore the stigma and related influencing factors in individuals with chronic insomnia disorder (CID).

Methods: A total of 70 CID patients and 70 healthy controls (CON) were enrolled in the study. All subjects completed the assessments of sleep, emotion, and cognition.

SSThe coexistence and diversity of Candidatus methylomirabilis oxyfera-like and anammox bacteria in sediments of an urban eutrophic lake.

Tangxun Lake is the largest urban lake in China, which is polluted by multiple wastewaters, and now is severely eutrophic. We detected diversity, abundance, and the coexistence of Candidatus Methylomirabilis oxyfera-like and anammox bacteria in different horizontal and vertical directions of the lake sediments through qPCR and clone library. Phylogenetic tree analysis showed that the Ca.

Baicalein induces the apoptosis of HCT116 human colon cancer cells via the upregulation of DEPP/Gadd45a and activation of MAPKs.

Baicalein has efficient antitumor properties and has been reported to promote the apoptosis of several human cancer cell lines. Decidual protein induced by progesterone (DEPP), a transcriptional target of Forkhead Box O, was originally identified from the human endometrial stromal cell cDNA library. However, the expression and physiological functions of DEPP in human colon cancer cells remain to be fully elucidated.