Efficacy, immunogenicity and safety of CoronaVac® in children and adolescents aged 6 months to 17 years: a multicenter, randomized, double-blind, placebo-controlled phase III clinical trial.

Safe and effective vaccines against COVID-19 for children and adolescents are needed. This international multicenter, randomized, double-blind, placebo-controlled, phase III clinical trial assessed the efficacy, immunogenicity, and safety of CoronaVac® in children and adolescents (NCT04992260). The study was carried out in Chile, South Africa, Malaysia, and the Philippines. The enrollment ran from September 10, 2021 to March 25, 2022. For efficacy assessment, the median follow-up duration from 14 days after the second dose was 169 days. A total of 11,349 subjects were enrolled. Two 3-µg injections of CoronaVac® or placebo were given 28 days apart. The primary endpoint was the efficacy of the CoronaVac®. The secondary endpoints were the immunogenicity and safety. The vaccine efficacy was 21.02% (95% CI: 1.65, 36.67). The level of neutralizing antibody in the vaccine group was significantly higher than that in the placebo group (GMT: 390.80 vs. 62.20, P <0.0001). Most adverse reactions were mild or moderate. All the severe adverse events were determined to be unrelated to the investigational products. In conclusion, in the Omicron-dominate period, a two-dose schedule of 3 µg CoronaVac® was found to be safe and immunogenic, and showed potential against symptomatic COVID-19 in healthy children and adolescents.

Estimation of Carleman operator from a univariate time series.

Reconstructing a nonlinear dynamical system from empirical time series is a fundamental task in data-driven analysis. One of the main challenges is the existence of hidden variables; we only have records for some variables, and those for hidden variables are unavailable. In this work, the techniques for Carleman linearization, phase-space embedding, and dynamic mode decomposition are integrated to rebuild an optimal dynamical system from time series for one specific variable. Using the Takens theorem, the embedding dimension is determined, which is adopted as the dynamical system's dimension. The Carleman linearization is then used to transform this finite nonlinear system into an infinite linear system, which is further truncated into a finite linear system using the dynamic mode decomposition technique. We illustrate the performance of this integrated technique using data generated by the well-known Lorenz model, the Duffing oscillator, and empirical records of electrocardiogram, electroencephalogram, and measles outbreaks. The results show that this solution accurately estimates the operators of the nonlinear dynamical systems. This work provides a new data-driven method to estimate the Carleman operator of nonlinear dynamical systems.

Synthesis and evaluation of neuroactive steroids with novel pharmacophore at C-21 let identify a compound with advantageous PK profile and higher EC50 and Emax as PAM on GABAA receptor.

Zuranolone (SAGE-217) is a neuroactive steroid (γ-aminobutyric acid)A (GABAA) receptor positive allosteric modulator (PAM) as the first oral drug approved by the FDA in 2023, which is used to treat patients with postpartum depression (PPD). SAGE-217 has a "black box" warning with impairing ability to drive or engage in other potentially hazardous activities. In addition, SAGE-217 can cause CNS depressant effects such as somnolence and confusion, suicidal thoughts and behavior and embryo-fetal toxicity. Based on the structure-activity relationship (SAR) of SAGE-217, a total of 28 neuroactive steroids with novel pharmacophore at C-21 modulated SAGE-217 derivatives were designed and synthesized. The biological activities were evaluated by both synaptic α1ß2γ2 GABAA receptor and extrasynaptic α4ß3δ GABAA receptor cell assays. The optimal compound S28 exhibited much more potent potency and similar efficacy at extrasynaptic GABAA receptor than SAGE-217. Different from above, compound S28 exhibited similar potency and lower efficacy at synaptic GABAA receptor than SAGE-217, which were consistent with the analysis of molecular docking and dynamics simulation results. The appropriate lower efficacy at synaptic GABAA receptor of compound S28 might contribute to reduce the side effects of excessive sedation. Furthermore, compound S28 was demonstrated to have excellent in vivo pharmacokinetic (PK) parameters, robust in vivo pharmacodynamic (PD) effects and good safety profiles. Therefore, compound S28 represents a potentially promising treatment of PPD candidate that warrants further investigation.

YAP represses the TEAD-NF-κB complex and inhibits the growth of clear cell renal cell carcinoma.

The Hippo pathway is generally understood to inhibit tumor growth by phosphorylating the transcriptional cofactor YAP to sequester it to the cytoplasm and reduce the formation of YAP-TEAD transcriptional complexes. Aberrant activation of YAP occurs in various cancers. However, we found a tumor-suppressive function of YAP in clear cell renal cell carcinoma (ccRCC). Using cell cultures, xenografts, and patient-derived explant models, we found that the inhibition of upstream Hippo-pathway kinases MST1 and MST2 or expression of a constitutively active YAP mutant impeded ccRCC proliferation and decreased gene expression mediated by the transcription factor NF-κB. Mechanistically, the NF-κB subunit p65 bound to the transcriptional cofactor TEAD to facilitate NF-κB-target gene expression that promoted cell proliferation. However, by competing for TEAD, YAP disrupted its interaction with NF-κB and prompted the dissociation of p65 from target gene promoters, thereby inhibiting NF-κB transcriptional programs. This cross-talk between the Hippo and NF-κB pathways in ccRCC suggests that targeting the Hippo-YAP axis in an atypical manner-that is, by activating YAP-may be a strategy for slowing tumor growth in patients.

Heterologous booster vaccination enhances antibody responses to SARS-CoV-2 by improving Tfh function and increasing B-cell clonotype SHM frequency.

Heterologous prime-boost has broken the protective immune response bottleneck of the COVID-19 vaccines. however, the underlying mechanisms have not been fully elucidated. Here, we investigated antibody responses and explored the response of germinal center (GC) to priming with inactivated vaccines and boosting with heterologous adenoviral-vectored vaccines or homologous inactivated vaccines in mice. Antibody responses were dramatically enhanced by both boosting regimens. Heterologous immunization induced more robust GC activation, characterized by increased Tfh cell populations and enhanced helper function. Additionally, increased B-cell activation and antibody production were observed in a heterologous regimen. Libra-seq was used to compare the differences of S1-, S2- and NTD-specific B cells between homologous and heterologous vaccination, respectively. S2-specific CD19+ B cells presented increased somatic hypermutations (SHMs), which were mainly enriched in plasma cells. Moreover, a heterologous booster dose promoted the clonal expansion of B cells specific to S2 and NTD regions. In conclusion, the functional role of Tfh and B cells following SARS-CoV-2 heterologous vaccination may be important for modulating antibody responses. These findings provide new insights for the development of SARS-CoV-2 vaccines that induce more robust antibody response.

Bavachinin, a main compound of Psoraleae Fructus, facilitates GSDMD-mediated pyroptosis and causes hepatotoxicity in mice.

Psoraleae Fructus (PF, Psoralea corylifolia L.), a traditional medicine with a long history of application, is widely used clinically for the treatment of various diseases. However, the reports of PF-related adverse reactions, such as hepatotoxicity, phototoxic dermatitis, and allergy, are increasing year by year, with liver injury being the mostly common. Our previous studies have demonstrated that PF and its preparations can cause liver injury in lipopolysaccharide (LPS)-mediated susceptibility mouse model, but the mechanism of PF-related liver injury is unclear. In this study, we showed that PF and bavachinin, a major component of PF, can directly induce the expression of caspase-1 and interleukin-1ß (IL-1ß), indicating that PF and bavachinin can directly triggered the activation of inflammasome. Furthermore, pretreatment with NLR family pyrin domain-containing 3 (NLRP3), NLR family CARD domain containing 4 (NLRC4) or absent in melanoma 2 (AIM2) inflammasome inhibitors, containing MCC950, ODN TTAGGG (ODN) and carnosol, all significantly reversed bavachinin-induced inflammasome activation. Mechanistically, bavachinin dose-dependently promote Gasdermin D (GSDMD) post-shear activation and then induce mitochondrial reactive oxygen species (mtROS) production and this effect is markedly inhibited by pretreatment with N-Acetylcysteine amide (NAC). In addition, combination treatment of LPS and bavachinin significantly induced liver injury in mice, but not LPS or bavachinin alone, and transcriptome analysis further validated these results. Thus, PF and bavachinin can induce the activation of inflammasome by promoting GSDMD cleavage and cause hepatotoxicity in mice. Therefore, PF, bavachinin, and PF-related preparations should be avoided in patients with inflammasome activation-associated diseases.

Multimodal integration of radiology and pathology signatures for distinguishing between aldosterone-producing adenomas and nonfunctional adrenal adenomas.

OBJECTIVE: To develop and validate a nomogram combining radiomics and pathology features to distinguish between aldosterone-producing adenomas (APAs) and nonfunctional adrenal adenomas (NF-AAs). METHODS: Consecutive patients diagnosed with adrenal adenomas via computed tomography (CT) or pathologic analysis between January 2011 and November 2022 were eligible for inclusion in this retrospective study. CT images and hematoxylin & eosin-stained slides were used for annotation and feature extraction. The selected radiomics and pathology features were used to develop a risk model using various machine learning models, and the area under the receiver operating characteristic curve (AUC) was determined to evaluate diagnostic performance. The predicted results from radiomics and pathology features were combined and visualized using a nomogram. RESULTS: A total of 211 patients (APAs, n = 59; NF-AAs, n = 152) were included in this study, with patients randomly divided into either the training set or the testing set at a ratio of 8:2. The ExtraTrees model yielded a sensitivity of 0.818, a specificity of 0.733, and an accuracy of 0.756 (AUC = 0.817; 95% confidence interval [CI]: 0.675-0.958) in the radiomics testing set and a sensitivity of 0.999, a specificity of 0.842, and an accuracy of 0.867 (AUC = 0.905, 95% CI: 0.792-1.000) in the pathology testing set. A nomogram combining radiomics and pathology features demonstrated a strong performance (AUC = 0.912; 95% CI: 0.807-1.000). CONCLUSION: A nomogram combining radiomics and pathology features demonstrated strong predictive accuracy and discrimination capability. This model may help clinicians to distinguish between APAs and NF-AAs.

Tryptanthrin suppresses multiple inflammasome activation to regulate NASH progression by targeting ASC protein.

BACKGROUND: The adaptor protein apoptosis-associated speck-like protein (ASC) containing a caspase recruitment domain (CARD) can be activated through pyrin domain (PYD) interactions between sensors and ASC, and through CARD interactions between caspase-1 and ASC. Although the majority of ternary inflammasome complexes depend on ASC, drugs targeting ASC protein remain scarce. After screening natural compounds from Isatidis Radixin, we found that tryptanthrin (TPR) could inhibit NLRP3-induced IL-1ß and caspase-1 production, but the underlying anti-inflammatory mechanisms remain to be elucidated. PURPOSE: The purpose of this study was to determine the impact of TPR on the NLRP3, NLRC4, and AIM2 inflammasomes and the underlying mechanisms. Additionally, the efficacy of TPR was analysed in the further course of methionine- and choline-deficient (MCD)-induced NASH and lipopolysaccharide (LPS)-induced sepsis models of mice. METHODS: In vitro studies used bone marrow-derived macrophages to assess the anti-inflammatory activity of TPR, and the techniques included western blot, testing of intracellular K+ and Ca2+, immunofluorescence, enzyme-linked immunosorbent assay (ELISA), co-immunoprecipitation, ASC oligomerization assay, surface plasmon resonance (SPR), and molecular docking. We used LPS-induced sepsis models and MCD-induced NASH models in vivo to evaluate the effectiveness of TPR in inhibiting inflammatory diseases. RESULTS: Our observations suggested that TPR could inhibit NLRP3, NLRC4, and AIM2 inflammasome activation. As shown in a mouse model of inflammatory diseases caused by MCD-induced NASH and LPS-induced sepsis, TPR significantly alleviated the progression of diseases. TPR interrupted the interactions between ASC and NLRP3/NLRC4/AIM2 in the co-immunoprecipitation experiment, and stable binding of TPR to ASC was also evident in SPR experiments. The underlying mechanisms of anti-inflammatory activities of TPR might be associated with targeting ASC, in particular, PYD domain of ASC. CONCLUSION: In general, the requirement for ASC in multiple inflammasome complexes makes TPR, as a novel broad-spectrum inflammasome inhibitor, potentially useful for treating a wide range of multifactorial inflammasome-related diseases.

Immunogenicity of intranasal vaccine based on SARS-CoV-2 spike protein during primary and booster immunizations in mice.

Mucosal immunity plays a crucial role in combating and controlling the spread of highly mutated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recombinant subunit vaccines have shown safety and efficacy in clinical trials, but further investigation is necessary to evaluate their feasibility as mucosal vaccines. This study developed a SARS-CoV-2 mucosal vaccine using spike (S) proteins from a prototype strain and the omicron variant, along with a cationic chitosan adjuvant, and systematically evaluated its immunogenicity after both primary and booster immunization in mice. Primary immunization through intraperitoneal and intranasal administration of the S protein elicited cross-reactive antibodies against prototype strains, as well as delta and omicron variants, with particularly strong effects observed after mucosal vaccination. In the context of booster immunization following primary immunization with inactivated vaccines, the omicron-based S protein mucosal vaccine resulted in a broader and more robust neutralizing antibody response in both serum and respiratory mucosa compared to the prototype vaccine, enhancing protection against different variants. These findings indicate that mucosal vaccination with the S protein has the potential to trigger a broader and stronger antibody response during primary and booster immunization, making it a promising strategy against respiratory pathogens.

Network Spreading from Network Dimension.

Continuous-state network spreading models provide critical numerical and analytic insights into transmission processes in epidemiology, rumor propagation, knowledge dissemination, and many other areas. Most of these models reflect only local features such as adjacency, degree, and transitivity, so can exhibit substantial error in the presence of global correlations typical of empirical networks. Here, we propose mitigating this limitation via a network property ideally suited to capturing spreading. This is the network correlation dimension, which characterizes how the number of nodes within range of a source typically scales with distance. Applying the approach to susceptible-infected-recovered processes leads to a spreading model which, for a wide range of networks and epidemic parameters, can provide more accurate predictions of the early stages of a spreading process than important established models of substantially higher complexity. In addition, the proposed model leads to a basic reproduction number that provides information about the final state not available from popular established models.

Effects and molecular mechanisms of polyethylene microplastic oxidation on wheat grain quality.

Polyethylene microplastics (PE MPs) are the main MPs in agricultural soils and undergo oxidation upon environmental exposure. However, the influence of MP oxidation on phytotoxicity (especially for crop fruit) is still limited. This study aimed to explore the effect of PE MP oxidation on crop toxicity. Herein, a combination of plant phenotyping, metabolomic, and transcriptomic approaches was used to evaluate the effects of low-oxidation PE (LOPE) and high-oxidation PE (HOPE) on wheat growth, grain quality, and related molecular mechanisms using pot experiments. The results showed that HOPE induced a stronger inhibition of wheat growth and reduction in protein content and mineral elements than LOPE. This was accompanied by root ultrastructural damage and downregulation of carbohydrate metabolism, translation, nutrient reservoir activity, and metal ion binding gene expression. Compared with HOPE, LOPE activated a stronger plant defense response by reducing the starch content by 22.87 %, increasing soluble sugar content by 44.93 %, and upregulating antioxidant enzyme genes and crucial metabolic pathways (e.g., starch and sucrose, linoleic acid, and phenylalanine metabolism). The presence of PE MPs in the environment exacerbates crop growth inhibition and fruit quality deterioration, highlighting the need to consider the environmental and food safety implications of MPs in agricultural soils.

Metabolism, Disposition, Excretion, and Potential Transporter Inhibition of 7-16, an Improving 5-HT2A Receptor Antagonist and Inverse Agonist for Parkinson's Disease.

Compound 7-16 was designed and synthesized in our previous study and was identified as a more potential selective 5-HT2A receptor antagonist and inverse agonist for treating Parkinson's disease psychosis (PDP). Then, the metabolism, disposition, and excretion properties of 7-16 and its potential inhibition on transporters were investigated in this study to highlight advancements in the understanding of its therapeutic mechanisms. The results indicate that a total of 10 metabolites of 7-16/[14C]7-16 were identified and determined in five species of liver microsomes and in rats using UPLC-Q Exactive high-resolution mass spectrometry combined with radioanalysis. Metabolites formed in human liver microsomes could be covered by animal species. 7-16 is mainly metabolized through mono-oxidation (M470-2) and N-demethylation (M440), and the CYP3A4 isozyme was responsible for both metabolic reactions. Based on the excretion data in bile and urine, the absorption rate of 7-16 was at least 74.7%. 7-16 had weak inhibition on P-glycoprotein and no effect on the transport activity of OATP1B1, OATP1B3, OAT1, OAT3, and OCT2 transporters. The comprehensive pharmacokinetic properties indicate that 7-16 deserves further development as a new treatment drug for PDP.

Distinguishing between aldosterone-producing adenomas and non-functional adrenocortical adenomas using the YOLOv5 network.

BACKGROUND: You Only Look Once version 5 (YOLOv5), a one-stage deep-learning (DL) algorithm for object detection and classification, offers high speed and accuracy for identifying targets. PURPOSE: To investigate the feasibility of using the YOLOv5 algorithm to non-invasively distinguish between aldosterone-producing adenomas (APAs) and non-functional adrenocortical adenomas (NF-ACAs) on computed tomography (CT) images. MATERIAL AND METHODS: A total of 235 patients who were diagnosed with ACAs between January 2011 and July 2022 were included in this study. Of the 215 patients, 81 (37.7%) had APAs and 134 (62.3%) had NF-ACAs' they were randomly divided into either the training set or the validation set at a ratio of 9:1. Another 20 patients, including 8 (40.0%) with APA and 12 (60.0%) with NF-ACA, were collected for the testing set. Five submodels (YOLOv5n, YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) of YOLOv5 were trained and evaluated on the datasets. RESULTS: In the testing set, the mAP_0.5 value for YOLOv5x (0.988) was higher than the values for YOLOv5n (0.969), YOLOv5s (0.965), YOLOv5m (0.974), and YOLOv5l (0.983). The mAP_0.5:0.95 value for YOLOv5x (0.711) was also higher than the values for YOLOv5n (0.587), YOLOv5s (0.674), YOLOv5m (0.671), and YOLOv5l (0.698) in the testing set. The inference speed of YOLOv5n was 2.4 ms in the testing set, which was the fastest among the five submodels. CONCLUSION: The YOLOv5 algorithm can accurately and efficiently distinguish between APAs and NF-ACAs on CT images, especially YOLOv5x has the best identification performance.

Collective behaviors of animal groups may stem from visual lateralization-Tending to obtain information through one eye.

Animal groups exhibit various captivating movement patterns, which manifest as intricate interactions among group members. Several models have been proposed to elucidate collective behaviors in animal groups. These models achieve a certain degree of efficacy; however, inconsistent experimental findings suggest insufficient accuracy. Experiments have shown that some organisms employ a single information channel and visual lateralization to glean knowledge from other individuals in collective movements. In this study, we consider individuals' visual lateralization and a single information channel and develop a self-propelled particle model to describe the collective behavior of large groups. The results suggest that homogeneous visual lateralization gives the group a strong sense of cohesiveness, thereby enabling diverse collective behaviors. As the overlapping field grows, the cohesiveness gradually dissipates. Inconsistent visual lateralization among group members can reduce the cohesiveness of the group, and when there is a high degree of heterogeneity in visual lateralization, the group loses their cohesiveness. This study also examines the influence of visual lateralization heterogeneity on specific formations, and the results indicate that the directional migration formation is responsive to such heterogeneity. We propose an information network to portray the transmission of information within groups, which explains the cohesiveness of groups and the sensitivity of the directional migration formation.

Novel selective agents for the degradation of AR/AR-V7 to treat advanced prostate cancer.

The androgen receptor AR antagonists, such as enzalutamide and apalutamide, are efficient therapeutics for the treatment of prostate cancer (PCa). Even though they are effective at first, resistance to both drugs occurs frequently. Resistance is mainly driven by aberrations of the AR signaling pathway including AR gene amplification and the expression of AR splice variants (e.g. AR-V7). This highlights the urgent need for alternative therapeutic strategies. Here, a total of 24 compounds were synthesized and biologically evaluated to disclose compound 20i, exhibiting potent AR antagonistic activities (IC50 = 172.85 ± 21.33 nM), promising AR/AR-V7 protein degradation potency, and dual targeting site of probably AR (ligand-binding domain, LBD and N-terminal domain, NTD). It potently inhibits cell growth with IC50 values of 4.87 ± 0.52 and 2.07 ± 0.34 µM in the LNCaP and 22RV1 cell lines, respectively, and exhibited effective tumor growth inhibition (TGI = 50.9 %) in the 22RV1 xenograft study. These data suggest that 20i has the potential for development as an AR/AR-V7 inhibitor with degradation ability to treat advanced prostate cancer.

Identification of disease-specific bio-markers through network-based analysis of gene co-expression: A case study on Alzheimer's disease.

Finding biomarker genes for complex diseases attracts persistent attention due to its application in clinics. In this paper, we propose a network-based method to obtain a set of biomarker genes. The key idea is to construct a gene co-expression network among sensitive genes and cluster the genes into different modules. For each module, we can identify its representative, i.e., the gene with the largest connectivity and the smallest average shortest path length to other genes within the module. We believe these representative genes could serve as a new set of potential biomarkers for diseases. As a typical example, we investigated Alzheimer's disease, obtaining a total of 16 potential representative genes, three of which belong to the non-transcriptome. A total of 11 out of these genes are found in literature from different perspectives and methods. The incipient groups were classified into two different subtypes using machine learning algorithms. We subjected the two subtypes to Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes analysis with healthy groups and moderate groups, respectively. The two sub-type groups were involved in two different biological processes, demonstrating the validity of this approach. This method is disease-specific and independent; hence, it can be extended to classify other kinds of complex diseases.

Compound Danshen Dripping Pill effectively alleviates cGAS-STING-triggered diseases by disrupting STING-TBK1 interaction.

BACKGROUND: The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon (IFN) genes (STING) pathway is critical in the innate immune system and can be mobilized by cytosolic DNA. The various inflammatory and autoimmune diseases progression is highly correlated with aberrant cGAS-STING pathway activation. While some cGAS-STING pathway inhibitor were identified, there are no drugs that can be applied to the clinic. Compound Danshen Dripping Pill (CDDP) has been successfully used in clinic around the world, but the most common application is limited to cardiovascular disease. Therefore, the purpose of the present investigation was to examine whether CDDP inhibits the cGAS-STING pathway and could be used as a therapeutic agent for multiple cGAS-STING-triggered diseases. METHODS: BMDMs, THP1 cells or Trex1-/- BMDMs were stimulated with various cGAS-STING-agonists after pretreatment with CDDP to detect the function of CDDP on IFN-ß and ISGs productionn. Next, we detect the influence on IRF3 and P65 nuclear translocation, STING oligomerization and STING-TBK1-IRF3 complex formation of CDDP. Additionally, the DMXAA-mediated activation mice model of cGAS-STING pathway was used to study the effects of CDDP. Trex1-/- mice model and HFD-mediated obesity model were established to clarify the efficacy of CDDP on inflammatory and autoimmune diseases. RESULTS: CDDP efficacy suppressed the IRF3 phosphorylation or the generation of IFN-ß, ISGs, IL-6 and TNF-α. Mechanistically, CDDP did not influence the STING oligomerization and IRF3-TBK1 and STING-IRF3 interaction, but remarkably eliminated the STING-TBK1 interaction, ultimately blocking the downstream responses. In addition, we also clarified that CDDP could suppress cGAS-STING pathway activation triggered by DMXAA, in vivo. Consistently, CDDP could alleviate multi-organ inflammatory responses in Trex1-/- mice model and attenuate the inflammatory disorders, incleding obesity-induced insulin resistance. CONCLUSION: CDDP is a specifically cGAS-STING pathway inhibitor. Furthermore, we provide novel mechanism for CDDP and discovered a clinical agent for the therapy of cGAS-STING-triggered inflammatory and autoimmune diseases.

Weighted Signed Networks Reveal Interactions between US Foreign Exchange Rates.

Correlations between exchange rates are valuable for illuminating the dynamics of international trade and the financial dynamics of countries. This paper explores the changing interactions of the US foreign exchange market based on detrended cross-correlation analysis. First, we propose an objective way to choose a time scale parameter appropriate for comparing different samples by maximizing the summed magnitude of all DCCA coefficients. We then build weighted signed networks under this optimized time scale, which can clearly display the complex relationships between different exchange rates. Our study shows negative cross-correlations have become pyramidally rare in the past three decades. Both the number and strength of positive cross-correlations have grown, paralleling the increase in global interconnectivity. The balanced strong triads are identified subsequently after the network centrality analysis. Generally, while the strong development links revealed by foreign exchange have begun to spread to Asia since 2010, Europe is still the center of world finance, with the euro and Danish krone consistently maintaining the closest balanced development relationship. Finally, we propose a fluctuation propagation algorithm to investigate the propagation pattern of fluctuations in the inferred exchange rate networks. The results show that, over time, fluctuation propagation patterns have become simpler and more predictable.

Application of multidisciplinary in situ simulation training in the treatment of acute ischemic stroke: a quality improvement project.

BACKGROUND: Ischemic stroke refers to a disorder in the blood supply to a local area of brain tissue for various reasons and is characterized by high morbidity, mortality, and disability. Early reperfusion of brain tissue at risk of injury is crucial for the treatment of acute ischemic stroke. The purpose of this study was to evaluate comfort levels in managing acute stroke patients with hypoxemia who required endotracheal intubation after multidisciplinary in situ simulation training and to shorten the door-to-image time. METHODS: This quality improvement project utilized a comprehensive multidisciplinary in situ simulation exercise. A total of 53 participants completed the two-day in situ simulation training. The main outcome was the self-reported comfort levels of participants in managing acute stroke patients with hypoxemia requiring endotracheal intubation before and after simulation training. A 5-point Likert scale was used to measure participant comfort. A paired-sample t-test was used to compare the mean self-reported comfort scores of participants, as well as the endotracheal intubation time and door-to-image time on the first and second days of in situ simulation training. The door-to-image time before and after the training was also recorded. RESULTS: The findings indicated that in situ simulation training could enhance participant comfort when managing acute stroke patients with hypoxemia who required endotracheal intubation and shorten door-to-image time. For the emergency management of hypoxemia or tracheal intubation, the mean post-training self-reported comfort score was significantly higher than the mean pre-training comfort score (hypoxemia: 4.53±0.64 vs. 3.62±0.69, t= -11.046, P<0.001; tracheal intubation: 3.98±0.72 vs. 3.43±0.72, t= -6.940, P<0.001). We also observed a decrease in the tracheal intubation and door-to-image time and a decreasing trend in the door-to-image time, which continued after the training. CONCLUSION: Our study demonstrates that the implementation of in situ simulation training in a clinical environment with a multidisciplinary approach may improve the ability and confidence of stroke team members, optimize the first-aid process, and effectively shorten the door-to-image time of stroke patients with emergency complications.

Main Control Factors of Fracture Propagation in Reservoir: A Review.

The fracture distribution and internal control factors after the fracturing of unconventional oil and gas reservoirs determine the reservoir reforming effect to a large extent. Based on the research of global scholars on the influencing factors of fracture propagation, comprehensive theoretical model, and numerical simulation, this Review systematically discusses the influence of internal geological factors and external engineering factors of unconventional oil and gas reservoir on fracture propagation behavior and summarizes the current problems and development trends in fracture research. The results show the following: (1) The fracture propagation is a comprehensive process constrained by lithology and mineral composition, water saturation, nonhomogeneity, natural weak surface, and ground stress. (2) External engineering factors have a meaningful control effect on fracture propagation; the type and temperature of fracturing fluids can also change the mechanical properties of different rocks, thus affecting the fracture propagation pattern. (3) The existing fracture propagation models have certain limitations, and their computational reliability still needs to be further verified. (4) Numerical simulation can break through the limitations of physical simulation, but different simulation methods have different shortcomings and applicability. In the future, we should focus on: (1) finding parameters to quantitatively characterize heterogeneity at the 3D level, which is an important direction to study the effect of heterogeneity on fracture propagation; (2) introducing computerized methods to establish a geological model that considers multiple factors and combining it with numerical simulation software to study fracture propagation; (3) considering the characteristics of fluid-liquid-solid phase comprehensively, establishing a suitable THL coupling equation; (4) how the interaction mode of fracturing fracture is combined with the natural fracture geometry, and how the fracture is affected by fracturing engineering parameters such as fluid injection rate and viscosity of fracturing fluid; and (5) geology-engineering dynamic integration, which is an important direction to be carried out in the future.