RESUMEN
To reveal the connections between the 2024 moment magnitude (Mw) 7.5 Noto earthquake in Japan and the seismicity swarms that preceded it, we investigated its rupture process through near-source waveform analysis and source imaging techniques, combining seismic and geodetic datasets. We found notable complexity in the initial rupture stages. A strong fault asperity, which remained unbroken in preceding seismic swarms, slowed down the rupture. Then, a second rupture initiated at the opposite edge of the asperity, and the asperity succumbed to double-pincer rupture fronts. The failure of this high-stress drop asperity drove the earthquake into a large-scale event. Our observations help unravel the crucial role of fault asperities in controlling swarm migration and rupture propagation and underscore the need for detailed seismological and interdisciplinary studies to assess seismic risk in swarm-prone regions.
RESUMEN
Using recent advancements in high-performance computing data assimilation to combine satellite InSAR data with numerical models, the prolonged unrest of the Sierra Negra volcano in the Galápagos was tracked to provide a fortuitous, but successful, forecast 5 months in advance of the 26 June 2018 eruption. Subsequent numerical simulations reveal that the evolution of the stress state in the host rock surrounding the Sierra Negra magma system likely controlled eruption timing. While changes in magma reservoir pressure remained modest (<15 MPa), modeled widespread Mohr-Coulomb failure is coincident with the timing of the 26 June 2018 moment magnitude 5.4 earthquake and subsequent eruption. Coulomb stress transfer models suggest that the faulting event triggered the 2018 eruption by encouraging tensile failure along the northern portion of the caldera. These findings provide a critical framework for understanding Sierra Negra's eruption cycles and evaluating the potential and timing of future eruptions.
RESUMEN
The transmission heterogeneity of an epidemic is associated with a complex mixture of host, pathogen and environmental factors. And it may indicate superspreading events to reduce the efficiency of population-level control measures and to sustain the epidemic over a larger scale and a longer duration. Methods have been proposed to identify significant transmission heterogeneity in historic epidemics based on several data sources, such as contact history, viral genomes and spatial information, which is sophisticated and may not be available, and more importantly ignore the temporal trend of transmission heterogeneity. Here we attempted to establish a convenient method to estimate real-time heterogeneity over an epidemic. Within the branching process framework, we introduced an instant-individualheterogenous infectiousness model to jointly characterized the variation in infectiousness both between individuals and among different times. With this model, we could simultaneously estimate the transmission heterogeneity and the reproduction number from incidence time series. We validated the model with both simulated data and five historic epidemics. Our estimates of the overall and real-time heterogeneities of the five epidemics were consistent with those presented in the literature. Additionally, our model is robust to the ubiquitous bias of under-reporting and misspecification of serial interval. By analyzing the recent data from South Africa, we found evidences that the Omicron might be of more significant transmission heterogeneity than the Delta. Our model based on incidence data was proved to be reliable in estimating the real-time transmission heterogeneity. Author summaryThe transmission of many infectious diseases is usually heterogeneous in time and space. Such transmission heterogeneity may indicate superspreading events (where some infected individuals transmit to disproportionately more susceptible than others), reduce the efficiency of the population-level control measures, and sustain the epidemic over a larger scale and a longer duration. Classical methods of monitoring epidemic spread centered on the reproduction number which represent the average transmission potential of the epidemic at the population level, but failed to reflect the systematic variation in transmission. Several recent methods have been proposed to identify significant transmission heterogeneity in the epidemics such as Ebola, MERS, COVID-19. However, these methods are developed based on some sophisticated information such as contact history, viral genome and spatial information, of the confirmed cases, which are typically field-specific and not easy to generalize. In this study, we proposed a simple and generic method of estimating transmission heterogeneity from incidence time series, which provided consistent estimation of heterogeneity with those records with sophisticated data. It also helps in exploring the transmission heterogeneity of the newly emerging variant of Omicron. Our model enhances current understanding of epidemic dynamics, and highlight the potential importance of targeted control measures.
RESUMEN
The COVID-19 outbreak in Xinfadi (XFD) Wholesale market in Beijing, China in June, 2020 caused 368 reported cases within 39 days. Genetic evidences indicated that imported SARS-CoV-2 (belong to the lineage B1.1.29) initiated this outbreak. However, the transmission route of the virus is still unknown. We obtained from public database three SARS-CoV-2 genomes isolated in XFD (XFD genomes) and adopted the leaf-dating method to calculate their expected collection dates using temporal calibrating information from other 241 genomes collected in mainland of China. All three XFD genomes were calculated to have earlier collection dates than the recorded (Bayes factor >1), and hence exhibited a lack of genetic divergence. We additionally combined the XFD genomes with other 225 genomes subsampled from those of the lineage B1.1.29, among which five sequences were also included for control analysis. Two of three XFD genomes were calculated to have earlier collection dates than the recorded (Bayes factor >1), while no control genomes provided such evidence. According to present understanding of SARS-CoV-2, a lack of genetic divergence is most likely due to being frozen. Considering the fact that the XFD outbreak started from a booth of frozen food, we judged that the XFD outbreak was caused by contaminated frozen food. Our results provided molecular evidence for the source of COVID-19 outbreak in Beijing XFD, which highlights new targets for SARS-CoV-2 surveillance for the public health.
RESUMEN
Objective:To evaluate the effect of resveratrol combined with γ-ray irradiation on the biological behavior of cervical cancer cells, and to explore its possible mechanism.Methods:The proliferation of cell populations after different concentrations of resveratrol solution±γ-ray irradiation was detected by CCK-8 assay. Scratch test and Transwell chamber test were used to detect cell migration and invasion. Flow cytometry and Annexin V-FITC/PI double staining were employed to assess cell apoptosis. Western blot was performed to measure the expression levels of PI3K, Akt, p-Akt, mTOR and p-mTOR proteins.Results:Compared with the normal control (NC) group, the resveratrol group±γ-ray irradiation could inhibit the proliferation, migration, and invasion and promote cell apoptosis of human cervical cancer Hela cells, and the combined effect was more obvious. Compared with the NC group, resveratrol and γ-ray irradiation could significantly down-regulate the expression levels of Bcl-2, PI3K, p-Akt and p-mTOR proteins, up-regulate the expression level of Bax protein, but did not significantly alter the expression levels of Akt and mTOR proteins in human cervic1 255al cancer Hela cells.Conclusions:Resveratrol combined with γ-ray irradiation can dramatically inhibit the proliferation, migration, invasion, and promote the apoptosis of cervical cancer Hela cells. The mechanism may be related to the inhibition of the PI3K/Akt/mTOR signaling pathway and down-regulating the expression levels of downstream related proteins.
RESUMEN
BackgroundCOVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics including heterogeneity is of vital importance for prediction and intervention of future epidemics. In addition, transmission heterogeneity usually envokes super spreading events (SSEs) where certain individuals infect large numbers of secondary cases. Till now, studies of transmission heterogeneity of COVID-19 and its underlying reason are far from reaching an agreement. MethodsWe collected information of all infected cases between January 21 and February 26, 2020 from official public sources in Tianjin, a metropolis of China. . Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k which characterized the transmission potential and heterogeneity, respectively. Furthermore, we studied the SSE in Tianjin outbreak and evaluated the effect of control measures undertaken by local government based on the heterogeneous model. ResultsA total of 135 confirmed cases (including 34 imported cases and 101 local infections) in Tianjin by February 26th 2020 entered the study. We grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of 4 generations. The estimated reproduction number R was at 0.67 (95%CI: 0.54~0.84), and the dispersion parameter k was at 0.25 (95% CI: 0.13~0.88). A super spreader causing six infections in Tianjin, was identified. In addition, our simulation results showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since January 28th. ConclusionsOur analysis suggested that the transmission of COVID-19 was subcritical but with significant heterogeneity and may incur SSE. More efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors, which is important for developing targeted measures to curb the pandemic.
RESUMEN
Objective:To Summarize mathematical and statistical models used in the area of infectious diseases modelling, to provide ideas and suggestions for the model-based analysis and decision-making of COVID-19.Methods:By reviewing the commonly used mathematical and statistical models in the analysis of infectious diseases, with a focus on the mathematical models of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) that have been published and their practical effects.Results:Infectious diseases modelling based on multi-source information has become the main research trend, and the published mathematical models of COVID-19 epidemic need to be improved in terms of accuracy and scalability.Conclusions:It is recommended to build a more advanced mathematical/statistical model by allowing for the characteristics of new coronaviruses and to use more informative data to improve the analysis and decision-making of the new epidemic.
RESUMEN
Objective@#To Summarize mathematical and statistical models used in the area of infectious diseases modelling, to provide ideas and suggestions for the model-based analysis and decision-making of COVID-19.@*Methods@#By reviewing the commonly used mathematical and statistical models in the analysis of infectious diseases, with a focus on the mathematical models of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) that have been published and their practical effects.@*Results@#Infectious diseases modelling based on multi-source information has become the main research trend, and the published mathematical models of COVID-19 epidemic need to be improved in terms of accuracy and scalability.@*Conclusions@#It is recommended to build a more advanced mathematical/statistical model by allowing for the characteristics of new coronaviruses and to use more informative data to improve the analysis and decision-making of the new epidemic.
RESUMEN
Objective@#To study the epidemiological characteristics and related factors of dyslipidemia among adult residents in Xinjiang Uygur Autonomous Region (Xinjiang) in 2013-2014.@*Methods@#A total of 4 120 adult residents consisting of Han and Uygur group aged over 18 years old were selected by using a stratified cluster random sampling method in 8 counties of Xinjiang from 2013 to 2014. The related factors of dyslipidemia were collected by questionnaire and physical measurement. The total cholesterol, triglyceride, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol were detected by enzyme method. Factors associated with dyslipidemia were analyzed by chi-squared test and a multivariate unconditioned logistic regression model adjusted for gender, urban or rural area, age-group, body mass index (BMI), central obesity, smoking, drinking, education attainment, diabetes mellitus and hypertension.@*Results@#The prevalence of dyslipidemia was 45.00% (1 854 cases). The prevalence of dyslipidemia was higher in Uygur group (47.80% (977/2 044)) than that in Han group (42.24% (877/2 076)) (χ2=12.84, P<0.001). The analysis showed that dyslipidemia was related with gender (OR=0.41, 95%CI: 0.33-0.51), urban area (OR=0.54, 95%CI: 0.39-0.76), BMI (overweight group (OR=1.52, 95%CI: 1.18-1.96); obesity group (OR=2.20, 95%CI: 1.64-2.96)), central obesity (OR=1.66, 95%CI: 1.29-2.14) and diabetes mellitus (OR=1.49, 95%CI: 1.06-2.11) in Uygur group. The analysis also showed that dyslipidemia was related with BMI (overweight group (OR=1.72, 95%CI: 1.32-2.25), obesity group (OR=2.60, 95%CI: 1.85-3.64)), central obesity (OR=1.45, 95%CI: 1.13-1.87), smoking (OR=1.46, 95%CI: 1.09-1.95), diabetes mellitus (OR=1.77, 95%CI: 1.38-2.25) and hypertension (OR=1.62, 95%CI: 1.31-2.00) in Han group.@*Conclusions@#The prevalence of dyslipidemia in Xinjiang was higher than the national average prevalence. The prevalence of dyslipidemia in Uygur group was significantly higher than that in Han group. The gender, living area, BMI, central obesity and diabetes mellitus were risk factors of dyslipidemia in Uygur group, and BMI, central obesity, smoking, diabetes mellitus and hypertension were risk factors of dyslipidemia in Han group in Xinjiang.
RESUMEN
Hainan is an island province in south China with a high frequency of unconventional emergencies due to its special geographic location and national military defense role. Given the limited transportation route from Hainan to the outside world, self-rescue is more important to Hainan Province than other provinces in China and it is therefore imperative to establish an independent, scientific as well as efficient provincal disaster medical system in Hainan. The regulatory role for vulnerability analysis/assessment has been demonstrated in establisment of disaster medical system in varoius countries and or regions. In this paper, we attempt to describe/propose how to adopt vulnerability assessment through mathematical modeling of major biophysical social vulnerability factors to establish an independent, scientific, effieicnt and comprehensive provincial disaster medical system in Hainan.
Asunto(s)
Humanos , China , Defensa Civil , Métodos , Planificación en Desastres , Métodos , Desastres , Servicios Médicos de Urgencia , Métodos , Geografía , Modelos OrganizacionalesRESUMEN
Objective To investigate the risk factors for persistent hemodynamic depression after carotid angioplasty and stenting(CAS). Methods Sixty-one patients with CAS were included. By univariate Logistic regression analysis,the influencing factors for persistent hemodynamic depression were analyzed,by stepwise Logistic regression analysis and adjustment for age and gender factors,the independent risk factors for persistent hemodynamic depression were analyzed. Results In 61 patients,25 cases had hypotension,25 cases had bradycardia,all for 41.0% incidence. According to the patients intraoperative and postoperative blood pressure,heart rate conditions,the duration of hemodynamic depression,the cases were divided into persistent hemodynamic depression group (20 cases) and no-persistent hemodynamic depression group(41 cases). Univariate Logistic regression analysis indicated that persistent hemodynamic depression influencing factors were the symptomatic stenosis, severe stenosis, using balloon dilatation, implantation of laser-carving stent(P<0.05). With adjustment for age and gender factors, stepwise Logistic regression analysis showed that using balloon dilatation, implantation of laser-carving stent were the independent risk factors for persistent hemodynamic depression (OR = 5.046,95%CI 1.342-18.977,P = 0.017;OR = 4.142,95%CI 1.151-14.902, P= 0.030),symptomatic stenosis was the independent protective factor for persistent hemodynamic depression (OR = 0.264,95% CI 0.073-0.964,P= 0.044). Conclusions Persistent hemodynamic depression after CAS is a common complication.CAS patients with using balloon dilatation, implantation of laser-carving stent are more susceptible to persistent hemodynamic depression, while symptomatic stenosis is its protective factor.
RESUMEN
We report on a Tm(3+)-doped fiber laser source operating at 1936.4 nm with a very narrow linewidth (50 pm) laser output. Up to 2.4 W cw laser power was obtained from an 82 cm long Tm(3+)-doped multimode-core fiber cladding pumped by a 792 nm laser diode (LD). The fiber laser cavity included a high-reflective dichroic and a low-reflective FBG output coupler. The multimode fiber Bragg grating (FBG) transmission spectrum and output laser spectrum were measured. By adjusting the distance between the dichroic and the Tm(3+)-doped fiber end, the multipeak laser spectrum changed to a single-peak laser spectrum.
