Effects of obstetric critical care simulation training on core competency and learning experience of midwives: A pilot quasi-experimental study.

AIM: This study aimed to investigate the effects of maternal critical care simulation training on the core competency and satisfaction of midwives in China. BACKGROUND: Midwives play an important role during the peripartum period. Simulation-based training could be an effective tool in improving the core competency of midwives when managing critical obstetric illnesses. DESIGN: A pilot pre- and post-course, quasi-experimental study in China. METHOD: In July 2022, 82 midwives completed a 2-day obstetric critical care simulation training and survey. Core competency was evaluated by a comprehensive score system, including response ability, communication ability, site control ability, critical thinking ability, team cooperation ability, forward-thinking ability, midwifery specialty ability, and error correction ability. We used the Simulation Effectiveness Tool-Modified (SET-M) to evaluate the learning experience and satisfaction. Descriptive analysis, McNemar χ2 test, and subject content analysis were used for data analysis. RESULTS: After the training, the core competency scores showed significant improvements in the case scenarios simulating shoulder dystocia, amniotic fluid embolism, and eclampsia (P < 0.05) but not postpartum hemorrhage (P > 0.05). The scores evaluated by the SET-M were all above 2.5 points. Some midwives preferred extended course duration, expanded course materials, and more active involvement in the simulation exercises. The midwives were generally highly satisfied with the training, but some expressed certain negative emotions, such as anxiety and nervousness. CONCLUSION: The high quality of scientifically constructed and implemented obstetric critical care simulation training courses could improve the core competency and satisfaction of midwives. Appropriate preparation and professional simulation teachers are required to reduce negative emotions and improve learning outcomes and experience.

In situ remediation mechanism of internal nitrogen and phosphorus regeneration and release in shallow eutrophic lakes by combining multiple remediation techniques.

Large anthropogenic inputs of N and P alter the nutrient cycle and exacerbate global eutrophication problems in aquatic ecosystems. This study in Lake Datong, China, investigates the remediation mechanism of multiple remediation technique combinations (dredging, adsorbent amendment, and planting aquatic vegetation) on sediment N and P loads based on two high-resolution sampling techniques (HR-Peeper and DGT) and P sequential extraction procedures. The results showed that high temperature and low dissolved oxygen considerably enhanced pore water dissolved reactive P (DRP) and NH4+ concentrations attributable to abundant Fe-P and organic matter content in the sediment. Fe reduction is critical for regulating pore water DRP release and promoting N removal. Overall, for Lake Datong, combining multiple remediation techniques is more effective in controlling sediment P loads (pore water DRP, P fluxes, forms of P, and labile P), from a long-term perspective, than a single remediation. Lanthanum-modified bentonite (LMB) inactivation treatment can transfer mobile P in the surface sediment into more refractory forms over time, thereby reducing the risk of sediment labile P release. However, it is difficult to effectively remediate internal P loads owing to inappropriate dredging depths and low biomass of aquatic vegetation. Future lake restoration practices should optimize the selection of different remediation technique combinations based on internal N and P pollution characteristics, while reducing external wastewater input. These results are important for understanding the remediation mechanisms of internal N and P and provide suggestions for sediment management of shallow eutrophic lakes.

Unifying structural signature of eukaryotic α-helical host defense peptides.

Diversity of α-helical host defense peptides (αHDPs) contributes to immunity against a broad spectrum of pathogens via multiple functions. Thus, resolving common structure-function relationships among αHDPs is inherently difficult, even for artificial-intelligence-based methods that seek multifactorial trends rather than foundational principles. Here, bioinformatic and pattern recognition methods were applied to identify a unifying signature of eukaryotic αHDPs derived from amino acid sequence, biochemical, and three-dimensional properties of known αHDPs. The signature formula contains a helical domain of 12 residues with a mean hydrophobic moment of 0.50 and favoring aliphatic over aromatic hydrophobes in 18-aa windows of peptides or proteins matching its semantic definition. The holistic α-core signature subsumes existing physicochemical properties of αHDPs, and converged strongly with predictions of an independent machine-learning-based classifier recognizing sequences inducing negative Gaussian curvature in target membranes. Queries using the α-core formula identified 93% of all annotated αHDPs in proteomic databases and retrieved all major αHDP families. Synthesis and antimicrobial assays confirmed efficacies of predicted sequences having no previously known antimicrobial activity. The unifying α-core signature establishes a foundational framework for discovering and understanding αHDPs encompassing diverse structural and mechanistic variations, and affords possibilities for deterministic design of antiinfectives.

[Effects of Transcutaneous Electrical Acupoint Stimulation for Depression in Late Pregnancy and Impacts on Inflammatory Cytokines].

OBJECTIVE: To assess the safety and efficacy of transcutaneous electrical acupoint stimulation (TEAS) for depression in late pregnancy and impacts on inflammatory cytokines. METHODS: A total of 150 pregnant women with depression in late pregnancy were randomized into a high intensity group (n＝52), a low intensity group (n＝49) and a control group (n＝49). TEAS was applied at bilateral Neiguan (PC 6) and Shenmen (HT 7) for 6 weeks. The intensities of TEAS in the high intensity group, the low intensity group and the control group were 10, 5 and 0 mA, respectively. During the process of TEAS, the blood pressure, pulse, uterine contraction and the fetal heart rate were recorded. Depression was evaluated by 24-item Hamilton depression scale (HAMD) before TEAS and after 2-week, 4-week, 6-week treatment. Serum levels of tumor necrosis factor-α (TNF-α), interleukin-1 ß (IL-1 ß) and IL-6 were detected by enzyme-linked immunosorbent assay (ELISA) before and after 6-week treatment. Delivery outcomes were observed. The correlation was analyzed between HAMD difference value and the diffe-rence values of TNF-α， IL-1 ß and IL-6, respectively. RESULTS: The blood pressure, pulse and fetal heart rate had no statistical significance before and after treatment in the three groups (P>0.05). The HAMD scores at all the time points were lower than that before treatment in the high intensity group (P<0.05), which were lower compared with those in the low intensity group and the control group (P<0.05). The HAMD score in the low intensity group decreased after 6-week treatment compared with that before treatment and was lower than that in the control group (P<0.05). The serum levels of IL-1 ß and IL-6 in the high intensity group decreased compared with those before treatment and were lower compared with those in the low intensity group and the control group after 6-week treatment (P<0.05). There was no significant difference in the deliver outcomes among the three groups (P>0.05). The variation of HAMD score did not have significant correlation with those of TNF-α， IL-1 ß and IL-6 (P>0.05). CONCLUSION: TEAS is safe and effective for depression in late pregnancy and can regulate the serum levels of IL-1 ß and IL-6 without influencing on delivery outcome.

A specific pharmacophore model of Aurora B kinase inhibitors and virtual screening studies based on it.

In this study, 3D-pharmacophore models of Aurora B kinase inhibitors have been developed by using HipHop and HypoGen modules in Catalyst software package. The best pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9911), consists of one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic aliphatic moiety and one ring aromatic feature. Hypo1 was validated by test set and cross-validation methods. And the specificity of Hypo1 to Aurora B inhibitors was examined with the use of selective inhibitors against Aurora B and its paralogue Aurora A. The results clearly indicate that Hypo1 can differentiate selective inhibitors of Aurora B from those of Aurora A, and the ring aromatic feature likely plays some important roles for the specificity of Hypo1. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge and Chinese Nature Product Database (CNPD) for identifying new inhibitors of Aurora B. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies to refine the retrieved hits, and some compounds selected from the top ranked hits have been suggested for further experimental assay studies.

Pharmacophore modeling and virtual screening for designing potential PLK1 inhibitors.

Pharmacophore models of Polo-like kinase-1 (PLK1) inhibitors have been established by using the HipHop and HypoGen algorithms implemented in the Catalyst software package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9895), consists of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic feature, and one hydrophobic aliphatic feature. Hypo1 was further validated by test set and cross validation method. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge, and Chinese Nature Product Database (CNPD). The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, a total of 20 compounds were selected and have been shifted to in vitro and in vivo studies. As far as we know, this is the first report on the pharmacophore modeling even the first publicly reported virtual screening study of PLK1 inhibitors.

Pharmacophore modelling and virtual screening for identification of new Aurora-A kinase inhibitors.

Aurora-A has been identified as one of the most attractive targets for cancer therapy and a considerable number of Aurora-A inhibitors have been reported recently. In order to clarify the essential structure-activity relationship for the known Aurora-A inhibitors as well as identify new lead compounds against Aurora-A, 3D pharmacophore models were developed based on the known inhibitors. The best hypothesis, Hypo1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, 39 compounds were purchased for further in vitro assay against several human tumour cell lines including A549, MCF-7, HepG2 and PC-3, in which Aurora-A is overexpressed. Two compounds show very low micromolar inhibition potency against some of these tumour cells. And they have been selected for further investigation.