Mechanism of action of Taohong Siwu decoction in the alleviation of primary dysmenorrhea.

Background: As one of the most common gynecological disorders, PD significantly impacts the quality of life for women. TSD, a well-known traditional Chinese medical prescription, has gained popularity for its use in treating gynecological cold coagulation and blood stasis syndromes such as PD. However, the lack of comprehensive data hinders our understanding of its molecular mechanism. Purpose: The objective of the present study is to investigate the therapeutic effects of TSD on PD and elucidate its plausible mechanism. Methods: HPLC was employed to confirm the presence of the principal metabolites of TSD. The rat model of PD was induced by OT exposure following IWM and EB pretreatment, and subsequently treated with TSD via gastric gavage. The effects and potential mechanisms of TSD on PD rats were explored, encompassing general behavior, morphological alterations in the uterus and ovaries, biochemical indicators in the uterus and serum, and levels of proteins related to the PI3K/AKT signaling pathway. Results: Gallic acid, hydroxysafflower yellow A, albiflorin, paeoniflorin, and ferulic acid were determined to be the primary active metabolites of TSD. The pharmacological studies yielded results indicating the successful establishment of the PD model in rats. Additionally, TSD demonstrated its ability to protect PD rats by ameliorating general behavior, mitigating pathological damage to uterine and ovarian tissues, and modulating the expression levels of correlated factors (PGE2, PGF2α, Ca2+, TXB2, IL-6, TNF-α, NO, and COX-2) as well as p-PI3K/PI3K and p-AKT/AKT proteins. Conclusion: TSD exhibited protective effects against PD in rats through its interaction with multiple targets including P13K/AKT signaling pathway, indicating that TSD holds therapeutic potential for PD treatment and providing evidence supporting the rational utilization of TSD.

Sharpening clinical decision support alert and reminder designs with MINDSPACE: A systematic review.

BACKGROUND: Clinical decision support (CDS) alerts and reminders aim to influence clinical decisions, yet they are often designed without considering human decision-making behaviour. While this behaviour is comprehensively described by behavioural economics (BE), the sheer volume of BE literature poses a challenge to designers when identifying behavioural effects with utility to alert and reminder designs. This study tackles this challenge by focusing on the MINDSPACE framework for behaviour change, which collates nine behavioural effects that profoundly influence human decision-making behaviour: Messenger, Incentives, Norms, Defaults, Salience, Priming, Affect, Commitment, and Ego. METHOD: A systematic review searching MEDLINE, Embase, PsycINFO, and CINAHL Plus to explore (i) the usage of MINDSPACE effects in alert and reminder designs and (ii) the efficacy of those alerts and reminders in influencing clinical decisions. The search queries comprised ten Boolean searches, with nine focusing on the MINDSPACE effects and one focusing on the term mindspace. RESULTS: 50 studies were selected from 1791 peer-reviewed journal articles in English from 1970 to 2022. Except for ego, eight of nine MINDSPACE effects were utilised to design alerts and reminders, with defaults and norms utilised the most in alerts and reminders, respectively. Overall, alerts and reminders informed by MINDSPACE effects showed an average 71% success rate in influencing clinical decisions (alerts 73%, reminders 69%). Most studies utilised a single effect in their design, with higher efficacy for alerts (64%) than reminders (41%). Others utilised multiple effects, showing higher efficacy for reminders (28%) than alerts (9%). CONCLUSION: This review presents sufficient evidence demonstrating the MINDSPACE framework's merits for designing CDS alerts and reminders with human decision-making considerations. The framework can adequately address challenges in identifying behavioural effects pertinent to the effective design of CDS alerts and reminders. The review also identified opportunities for future research into other relevant effects (e.g., framing).

Predicting Patient Length of Stay in Australian Emergency Departments Using Data Mining.

Length of Stay (LOS) is an important performance metric in Australian Emergency Departments (EDs). Recent evidence suggests that an LOS in excess of 4 h may be associated with increased mortality, but despite this, the average LOS continues to remain greater than 4 h in many EDs. Previous studies have found that Data Mining (DM) can be used to help hospitals to manage this metric and there is continued research into identifying factors that cause delays in ED LOS. Despite this, there is still a lack of specific research into how DM could use these factors to manage ED LOS. This study adds to the emerging literature and offers evidence that it is possible to predict delays in ED LOS to offer Clinical Decision Support (CDS) by using DM. Sixteen potentially relevant factors that impact ED LOS were identified through a literature survey and subsequently used as predictors to create six Data Mining Models (DMMs). An extract based on the Victorian Emergency Minimum Dataset (VEMD) was used to obtain relevant patient details and the DMMs were implemented using the Weka Software. The DMMs implemented in this study were successful in identifying the factors that were most likely to cause ED LOS > 4 h and also identify their correlation. These DMMs can be used by hospitals, not only to identify risk factors in their EDs that could lead to ED LOS > 4 h, but also to monitor these factors over time.

High-Performance All-Polymer Photodetectors Enabled by New Random Terpolymer Acceptor with Fine-Tuned Molecular Weight.

Reducing the dark current density and enhancing the overall performance of the device is the focal point in research for organic photodetectors. Two novel random terpolymers (P3 and P4) with different molecular weights are synthesized and evaluated as acceptors in bulk heterojunction (BHJ) polymer photodetectors. Compared with known acceptor materials, such as N2200 (P1) and F-N2200 (P2), polymer P4 has a lower lowest unoccupied molecular orbital (LUMO) energy level, favorable morphology, and good miscibility with a donor material J71, which leads to proper phase separation of the blend film and better dissociation of excitons and transport of carriers. Therefore, a considerably low dark current density (Jd) of 1.9 × 10-10 A/cm2 and a high specific detectivity (D*) of 1.8 × 1013 cm Hz1/2/W (also "Jones") at 580 nm under a -0.1 V bias are realized for the P4-based photodetector. More importantly, the device also exhibits a fast response speed (τr/τf = 1.24/1.87 µs) and a wide linear dynamic range (LDR) of 109.2 dB. This work demonstrates that high-performance all-polymer photodetectors with ideal morphology can be realized by random polymer acceptors with a fine-tuned molecular weight.

A systematic literature review on unnecessary diagnostic testing: The role of ICT use.

BACKGROUND: The negative impact of unnecessary diagnostic tests on healthcare systems and patients has been widely recognized. Medical researchers in various countries have been devoting effort to reduce unnecessary diagnostic tests by using different types of interventions, including information and communications technology-based (ICT-based) intervention, educational intervention, audit and feedback, the introduction of guidelines or protocols, and the reward and punishment of staff. We conducted a review of ICT based interventions and a comparative analysis of their relative effectiveness in reducing unnecessary tests. METHOD: A systematic Boolean search in PubMed, EMBase and EBSCOhost research databases was performed. Keyword search and citation analysis were also conducted. Empirical studies reporting ICT based interventions, and their implications on relative effectiveness in reducing unnecessary diagnostic tests (pathology tests or medical imaging) were evaluated independently by two reviewers based on a rigorously developed coding protocol. RESULTS: 92 research articles from peer-reviewed journals were identified as eligible. 47 studies involved a single-method intervention and 45 involved multi-method interventions. Regardless of the number of interventions involved in the studies, ICT-based interventions were utilized by 71 studies and 59 of them were shown to be effective in reducing unnecessary testing. A clinical decision support (CDS) tool appeared to be the most adopted ICT approach, with 46 out of 71 studies using CDS tools. The CDS tool showed effectiveness in reducing test volume in 38 studies and reducing cost in 24 studies. CONCLUSIONS: This review investigated five frequently utilized intervention methods, ICT-based, education, introduction of guidelines or protocols, audit and feedback, and reward and punishment. It provides in-depth analysis of the efficacy of different types of interventions and sheds insights about the benefits of ICT based interventions, especially those utilising CDS tools, to reduce unnecessary diagnostic testing. The replicability of the studies is limited due to the heterogeneity of the studies in terms of context, study design, and targeted types of tests.