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1.
J Korean Med Sci ; 36(27): e197, 2021 Jul 12.
Artículo en Inglés | MEDLINE | ID: mdl-34254476

RESUMEN

We used the nationwide claims database to calculate the incidence of thrombotic events and predict their overall 2-week incidence. From 2006 to 2020, the incidence of deep vein thrombosis (DVT), pulmonary embolism (PE), and disseminated intravascular coagulation (DIC) tended to increase. Unlike intracranial venous thrombosis (ICVT) and intracranial thrombophlebitis (ICTP), which showed no age difference, other venous embolism, and thrombosis (OVET), DIC, DVT, and PE were significantly more common in over 65 years. The overall 2-week incidence of ICVT was 0.21/1,000,000 (95% confidence interval [CI], 0.11-0.32). ICTP, OVET, DIC, DVT and PE were expected to occur in 0.08 (95% CI, 0.02-0.14), 7.66 (95% CI, 6.08-9.23), 5.95 (95% CI, 4.88-7.03), 13.28 (95% CI, 11.92-14.64), 14.09 (95% CI, 12.80-15.37) per 1,000,000, respectively. To date, of 8,548,231 patients vaccinated with ChAdOx1 nCoV-19 in Korea, two had confirmed thrombosis with thrombocytopenia syndrome within 2 weeks. The observed incidence of ICVT after vaccination was 0.23/1,000,000.


Asunto(s)
Vacunas contra la COVID-19/efectos adversos , Coagulación Intravascular Diseminada/inducido químicamente , Embolia Pulmonar/inducido químicamente , Tromboembolia/inducido químicamente , Vacunación/efectos adversos , Trombosis de la Vena/inducido químicamente , Anciano , Causalidad , Trastornos Cerebrovasculares/epidemiología , Coagulación Intravascular Diseminada/epidemiología , Femenino , Humanos , Incidencia , Trombosis Intracraneal/epidemiología , Masculino , Persona de Mediana Edad , Modelos Teóricos , Embolia Pulmonar/epidemiología , República de Corea/epidemiología , Trombocitopenia/inducido químicamente , Trombocitopenia/epidemiología , Tromboembolia/epidemiología , Trombosis de la Vena/epidemiología
2.
Sci Rep ; 11(1): 14407, 2021 07 13.
Artículo en Inglés | MEDLINE | ID: mdl-34257366

RESUMEN

Prone position (PP) is known to improve oxygenation and reduce mortality in COVID-19 patients. This systematic review and meta-analysis aimed to determine the effects of PP on respiratory parameters and outcomes. PubMed, EMBASE, ProQuest, SCOPUS, Web of Sciences, Cochrane library, and Google Scholar were searched up to 1st January 2021. Twenty-eight studies were included. The Cochran's Q-test and I2 statistic were assessed heterogeneity, the random-effects model was estimated the pooled mean difference (PMD), and a meta-regression method has utilized the factors affecting heterogeneity between studies. PMD with 95% confidence interval (CI) of PaO2/FIO2 Ratio in before-after design, quasi-experimental design and in overall was 55.74, 56.38, and 56.20 mmHg. These values for Spo2 (Sao2) were 3.38, 17.03, and 7.58. PP in COVID-19 patients lead to significantly decrease of the Paco2 (PMD: - 8.69; 95% CI - 14.69 to - 2.69 mmHg) but significantly increase the PaO2 (PMD: 37.74; 95% CI 7.16-68.33 mmHg). PP has no significant effect on the respiratory rate. Based on meta-regression, the study design has a significant effect on the heterogeneity of Spo2 (Sao2) (Coefficient: 12.80; p < 0.001). No significant associations were observed for other respiratory parameters with sample size and study design. The pooled estimate for death rate and intubation rates were 19.03 (8.19-32.61) and 30.68 (21.39-40.75). The prone positioning was associated with improved oxygenation parameters and reduced mortality and intubation rate in COVID-19 related respiratory failure.


Asunto(s)
COVID-19/mortalidad , COVID-19/fisiopatología , Posición Prona/fisiología , COVID-19/terapia , Humanos , Intubación Intratraqueal/estadística & datos numéricos , Modelos Teóricos , Insuficiencia Respiratoria/mortalidad , Insuficiencia Respiratoria/fisiopatología , Insuficiencia Respiratoria/terapia
3.
Sci Rep ; 11(1): 14488, 2021 07 14.
Artículo en Inglés | MEDLINE | ID: mdl-34262069

RESUMEN

Since its emergence, the phenomenon of SARS-CoV-2 transmission by seemingly healthy individuals has become a major challenge in the effort to achieve control of the pandemic. Identifying the modes of transmission that drive this phenomenon is a perquisite in devising effective control measures, but to date it is still under debate. To address this problem, we have formulated a detailed mathematical model of discrete human actions (such as coughs, sneezes, and touching) and the continuous decay of the virus in the environment. To take into account those discrete and continuous events we have extended the common modelling approach and employed a hybrid stochastic mathematical framework. This allowed us to calculate higher order statistics which are crucial for the reconstruction of the observed distributions. We focused on transmission within a household, the venue with the highest risk of infection and validated the model results against the observed secondary attack rate and the serial interval distribution. Detailed analysis of the model results identified the dominant driver of pre-symptomatic transmission as the contact route via hand-face transfer and showed that wearing masks and avoiding physical contact are an effective prevention strategy. These results provide a sound scientific basis to the present recommendations of the WHO and the CDC.


Asunto(s)
COVID-19/prevención & control , COVID-19/transmisión , Portador Sano/prevención & control , Portador Sano/transmisión , Trazado de Contacto , Composición Familiar , Humanos , Higiene , Incidencia , Máscaras , Modelos Teóricos , Pandemias/prevención & control , Cuarentena , Factores de Riesgo , SARS-CoV-2
4.
Genes (Basel) ; 12(7)2021 06 25.
Artículo en Inglés | MEDLINE | ID: mdl-34202032

RESUMEN

Peripheral blood transcriptome is a highly promising area for biomarker development. However, transcript abundances (TA) in these cell mixture samples are confounded by proportions of the component leukocyte subpopulations. This poses a challenge to clinical applications, as the cell of origin of any change in TA is not known without prior cell separation procedure. We developed a framework to develop a cell-type informative TA biomarkers which enable determination of TA of a single cell-type (B lymphocytes) directly in cell mixture samples of peripheral blood (e.g., peripheral blood mononuclear cells, PBMC) without the need for subpopulation separation. It is applicable to a panel of genes called B cell informative genes. Then a ratio of two B cell informative genes (a target gene and a stably expressed reference gene) obtained in PBMC was used as a new biomarker to represent the target gene expression in purified B lymphocytes. This approach, which eliminates the tedious procedure of cell separation and directly determines TA of a leukocyte subpopulation in peripheral blood samples, is called the Direct LS-TA method. This method is applied to gene expression datasets collected in influenza vaccination trials as early predictive biomarkers of seroconversion. By using TNFRSF17 or TXNDC5 as the target genes and TNFRSF13C or FCRLA as the reference genes, the Direct LS-TA B cell biomarkers were determined directly in the PBMC transcriptome data and were highly correlated with TA of the corresponding target genes in purified B lymphocytes. Vaccination responders had almost a 2-fold higher Direct LS-TA biomarker level of TNFRSF17 (log 2 SMD = 0.84, 95% CI = 0.47-1.21) on day 7 after vaccination. The sensitivity of these Direct LS-TA biomarkers in the prediction of seroconversion was greater than 0.7 and area-under curves (AUC) were over 0.8 in many datasets. In this paper, we report a straightforward approach to directly estimate B lymphocyte gene expression in PBMC, which could be used in a routine clinical setting. Moreover, the method enables the practice of precision medicine in the prediction of vaccination response. More importantly, seroconversion could now be predicted as early as day 7. As the acquired immunology pathway is common to vaccination against influenza and COVID-19, these biomarkers could also be useful to predict seroconversion for the new COVID-19 vaccines.


Asunto(s)
Linfocitos B/fisiología , Expresión Génica , Vacunas contra la Influenza/inmunología , Seroconversión/genética , Receptor del Factor Activador de Células B/genética , Biomarcadores/análisis , Vacunas contra la COVID-19/inmunología , Biología Computacional/métodos , Bases de Datos Genéticas , Humanos , Leucocitos Mononucleares/fisiología , Modelos Teóricos , Metaanálisis en Red , Proteína Disulfuro Isomerasas/genética , Curva ROC , Receptores Fc/genética , Seroconversión/fisiología
5.
Int J Mol Sci ; 22(13)2021 Jun 25.
Artículo en Inglés | MEDLINE | ID: mdl-34202115

RESUMEN

The literature indicates the existence of a relationship between rhamnolipids and bacterial biofilm, as well as the ability of selected bacteria to produce rhamnolipids and alginate. However, the influence of biosurfactant molecules on the mechanical properties of biofilms are still not fully understood. The aim of this research is to determine the effect of rhamnolipids concentration, CaCl2 concentration, and ionic cross-linking time on the mechanical properties of alginate hydrogels using a Box-Behnken design. The mechanical properties of cross-linked alginate hydrogels were characterized using a universal testing machine. It was assumed that the addition of rhamnolipids mainly affects the compression load, and the value of this parameter is lower for hydrogels produced with biosurfactant concentration below CMC than for hydrogels obtained in pure water. In contrast, the addition of rhamnolipids in an amount exceeding CMC causes an increase in compression load. In bacterial biofilms, the presence of rhamnolipid molecules does not exceed the CMC value, which may confirm the influence of this biosurfactant on the formation of the biofilm structure. Moreover, rhamnolipids interact with the hydrophobic part of the alginate copolymer chains, and then the hydrophilic groups of adsorbed biosurfactant molecules create additional calcium ion trapping sites.


Asunto(s)
Alginatos/química , Bacterias/crecimiento & desarrollo , Biopelículas/crecimiento & desarrollo , Glucolípidos/química , Hidrogeles/química , Líquidos Iónicos/química , Algoritmos , Modelos Teóricos
6.
Int J Mol Sci ; 22(13)2021 Jun 24.
Artículo en Inglés | MEDLINE | ID: mdl-34202734

RESUMEN

The electrochemical behavior and the interaction of the immunosuppressive drug azathioprine (AZA) with deoxyribonucleic acid (DNA) were investigated using voltammetric techniques, mass spectrometry (MS), and scanning electron microscopy (SEM). The redox mechanism of AZA on glassy carbon (GC) was investigated using cyclic and differential pulse (DP) voltammetry. It was proven that the electroactive center of AZA is the nitro group and its reduction mechanism is a diffusion-controlled process, which occurs in consecutive steps with formation of electroactive products and involves the transfer of electrons and protons. A redox mechanism was proposed and the interaction of AZA with DNA was also investigated. Morphological characterization of the DNA film on the electrode surface before and after interaction with AZA was performed using scanning electron microscopy. An electrochemical DNA biosensor was employed to study the interactions between AZA and DNA with different concentrations, incubation times, and applied potential values. It was shown that the reduction of AZA molecules bound to the DNA layer induces structural changes of the DNA double strands and oxidative damage, which were recognized through the occurrence of the 8-oxo-deoxyguanosine oxidation peak. Mass spectrometry investigation of the DNA film before and after interaction with AZA also demonstrated the formation of AZA adducts with purine bases.


Asunto(s)
Azatioprina/química , Azatioprina/metabolismo , ADN/química , ADN/metabolismo , Oxidación-Reducción , Algoritmos , Azatioprina/farmacología , Técnicas Biosensibles , Fenómenos Químicos , Sustancias Macromoleculares/química , Sustancias Macromoleculares/ultraestructura , Espectrometría de Masas , Modelos Teóricos
7.
BMC Med ; 19(1): 162, 2021 07 13.
Artículo en Inglés | MEDLINE | ID: mdl-34253200

RESUMEN

BACKGROUND: When three SARS-CoV-2 vaccines came to market in Europe and North America in the winter of 2020-2021, distribution networks were in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation was critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs likely require that distribution is prioritized to the elderly, health care workers, teachers, essential workers, and individuals with comorbidities putting them at risk of severe clinical progression. METHODS: We evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not have been included in the first round of vaccination. And, we account for age-specific immune patterns in both states at the time of the start of the vaccination program. Our analysis assumes that health systems during winter 2020-2021 had equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. RESULTS: We find that allocating a substantial proportion (>75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. This result is robust to different profiles of waning vaccine efficacy and several different assumptions on age mixing during and after lockdown periods. As we do not explicitly model other high-mortality groups, our results on vaccine allocation apply to all groups at high risk of mortality if infected. A median of 327 to 340 deaths can be avoided in Rhode Island (3444 to 3647 in Massachusetts) by optimizing vaccine allocation and vaccinating the elderly first. The vaccination campaigns are expected to save a median of 639 to 664 lives in Rhode Island and 6278 to 6618 lives in Massachusetts in the first half of 2021 when compared to a scenario with no vaccine. A policy of vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and would result in 0.5% to 1% reductions in cumulative hospitalizations and deaths by mid-2021. CONCLUSIONS: Assuming high vaccination coverage (>28%) and no major changes in distancing, masking, gathering size, hygiene guidelines, and virus transmissibility between 1 January 2021 and 1 July 2021 a combination of vaccination and population immunity may lead to low or near-zero transmission levels by the second quarter of 2021.


Asunto(s)
Vacunas contra la COVID-19/provisión & distribución , COVID-19 , Control de Enfermedades Transmisibles/organización & administración , Asignación de Recursos para la Atención de Salud/organización & administración , Asignación de Recursos/organización & administración , Cobertura de Vacunación , Vacunación , Factores de Edad , COVID-19/epidemiología , COVID-19/prevención & control , Humanos , Incidencia , Massachusetts/epidemiología , Modelos Teóricos , Salud Pública/métodos , Salud Pública/normas , Rhode Island/epidemiología , SARS-CoV-2 , Vacunación/métodos , Vacunación/estadística & datos numéricos , Cobertura de Vacunación/estadística & datos numéricos , Cobertura de Vacunación/provisión & distribución
8.
BMC Infect Dis ; 21(1): 658, 2021 Jul 07.
Artículo en Inglés | MEDLINE | ID: mdl-34233622

RESUMEN

BACKGROUND: The reproduction number is one of the most crucial parameters in determining disease dynamics, providing a summary measure of the transmission potential. However, estimating this value is particularly challenging owing to the characteristics of epidemic data, including non-reproducibility and incompleteness. METHODS: In this study, we propose mathematical models with different population structures; each of these models can produce data on the number of cases of the influenza A(H1N1)pdm09 epidemic in South Korea. These structured models incorporating the heterogeneity of age and region are used to estimate the reproduction numbers at various terminal times. Subsequently, the age- and region-specific reproduction numbers are also computed to analyze the differences illustrated in the incidence data. RESULTS: Incorporation of the age-structure or region-structure allows for robust estimation of parameters, while the basic SIR model provides estimated values beyond the reasonable range with severe fluctuation. The estimated duration of infectious period using age-structured model is around 3.8 and the reproduction number was estimated to be 1.6. The estimated duration of infectious period using region-structured model is around 2.1 and the reproduction number was estimated to be 1.4. The estimated age- and region-specific reproduction numbers are consistent with cumulative incidence for corresponding groups. CONCLUSIONS: Numerical results reveal that the introduction of heterogeneity into the population to represent the general characteristics of dynamics is essential for the robust estimation of parameters.


Asunto(s)
Subtipo H1N1 del Virus de la Influenza A , Gripe Humana/epidemiología , Gripe Humana/transmisión , Adolescente , Adulto , Número Básico de Reproducción/estadística & datos numéricos , Epidemias , Humanos , Incidencia , Modelos Teóricos , República de Corea/epidemiología , Adulto Joven
9.
BMC Res Notes ; 14(1): 263, 2021 Jul 08.
Artículo en Inglés | MEDLINE | ID: mdl-34238337

RESUMEN

OBJECTIVES: We explore the existence of a fixed point as well as the uniqueness of a mapping in an ordered b-metric space using a generalized [Formula: see text]-weak contraction. In addition, some results are posed on a coincidence point and a coupled coincidence point of two mappings under the same contraction condition. These findings generalize and build on a few recent studies in the literature. At the end, we provided some examples to back up our findings. RESULT: In partially ordered b-metric spaces, it is discussed how to obtain a fixed point and its uniqueness of a mapping, and also investigated the existence of a coincidence point and a coupled coincidence point for two mappings that satisfying generalized weak contraction conditions.


Asunto(s)
Algoritmos , Modelos Teóricos
10.
Artículo en Inglés | MEDLINE | ID: mdl-34204132

RESUMEN

Health and social services (HSS) are now, more than ever, at the center of the debate of public policy. We are interested in studying the HSS services innovations from the networked-governance strategy standpoint. With this research, we contribute by analyzing the criteria leading to the formation of HSS public service innovation networks (HSS PSINs). These criteria are important because they may result in the much-needed empirical foundation of the metagovernance of public networks for sustainable innovation. Our analysis rests on neo-Schumpeterian interpretations of product, process, organizational, market, and input innovations, and their characteristics. By an empirical partial least squares structural equations model, we present here the relationships between those characteristics and HSS PSINs. Our intent is that these relationships become clearer, and help enhance HSS PSINs metagovernance-i.e., their control, democratic legitimacy, and accountability by public decision-makers. Hence, our research supports the voices for an extended use of networks for policy and service collaborative innovation for sustainability.


Asunto(s)
Investigación sobre Servicios de Salud , Servicio Social , Humanos , Modelos Teóricos , Innovación Organizacional , Política Pública , Responsabilidad Social
11.
PLoS One ; 16(7): e0252384, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34214101

RESUMEN

Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring efficient resource allocation and treatment planning. This study aimed to develop and compare prognosis prediction machine learning models based on invasive laboratory and noninvasive clinical and demographic data from patients' day of admission. Three Support Vector Machine (SVM) models were developed and compared using invasive, non-invasive, and both groups. The results suggested that non-invasive features could provide mortality predictions that are similar to the invasive and roughly on par with the joint model. Feature inspection results from SVM-RFE and sparsity analysis displayed that, compared with the invasive model, the non-invasive model can provide better performances with a fewer number of features, pointing to the presence of high predictive information contents in several non-invasive features, including SPO2, age, and cardiovascular disorders. Furthermore, while the invasive model was able to provide better mortality predictions for the imminent future, non-invasive features displayed better performance for more distant expiration intervals. Early mortality prediction using non-invasive models can give us insights as to where and with whom to intervene. Combined with novel technologies, such as wireless wearable devices, these models can create powerful frameworks for various medical assignments and patient triage.


Asunto(s)
COVID-19/mortalidad , Pandemias , SARS-CoV-2 , Máquina de Vectores de Soporte , Adulto , Anciano , Anciano de 80 o más Años , Comorbilidad , Registros Electrónicos de Salud , Femenino , Predicción , Humanos , Masculino , Persona de Mediana Edad , Modelos Teóricos , Riesgo , Índice de Severidad de la Enfermedad , Evaluación de Síntomas , Triaje , Adulto Joven
12.
Eur J Radiol ; 141: 109831, 2021 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-34218128

RESUMEN

PURPOSE: To evaluate the effectiveness of a mathematical model for histogram analysis of DCE-MRI in distinguishing responders from non-responders during RA drug treatment. METHOD: Twenty-three consecutive RA patients with clinically active inflammation prospectively underwent DCE-MRI at baseline and after treatment. Manual segmentation of the enhanced synovium was performed on the last phase of DCE-MRI. The voxel-based contrast enhancement was calculated in each phase to obtain 75th percentile values. Kinetic curves made from the 75th percentile values were fitted to mathematical model as follows, ΔS(t) = A(1 - e-αt)e-ßt, where A is the upper limit of signal intensity (%), α (sec-1) is the rate of signal increase, and ß (sec-1) is the rate of signal decrease during washout. AUC30 was calculated by integration of 30 s. SER was calculated as the signal intensity at the initial time point (t = 60) relative to the delayed time point (t = 300). The volumes of enhanced synovium (sum of the number of voxels) were also calculated. RESULTS: After treatment, α, Aα, AUC30 and SER were significantly lower in the responder group than in the non-responder group (p = 0.033, 0.024, 0.015, and 0.007). The p value of SER was lowest. Aα, AUC30, and the volume of enhanced synovium had significantly larger changes from baseline to after treatment in the responder group than in the non-responder group (p = 0.045, 0.017, and 0.008). The volume of enhanced synovium had the lowest p value. CONCLUSIONS: SER after treatment and change in the volume of enhanced synovium might be effective for distinguishing responders from non-responders.


Asunto(s)
Artritis Reumatoide , Preparaciones Farmacéuticas , Artritis Reumatoide/diagnóstico por imagen , Artritis Reumatoide/tratamiento farmacológico , Medios de Contraste , Humanos , Imagen por Resonancia Magnética , Modelos Teóricos
13.
Math Biosci Eng ; 18(4): 3790-3812, 2021 04 30.
Artículo en Inglés | MEDLINE | ID: mdl-34198413

RESUMEN

We propose a mathematical model based on a system of differential equations, which incorporates the impact of the chronic health conditions of the host population, to investigate the transmission dynamics of COVID-19. The model divides the total population into two groups, depending on whether they have underlying conditions, and describes the disease transmission both within and between the groups. As an application of this model, we perform a case study for Hamilton County, the fourth-most populous county in the US state of Tennessee and a region with high prevalence of chronic conditions. Our data fitting and simulation results quantify the high risk of COVID-19 for the population group with underlying health conditions. The findings suggest that weakening the disease transmission route between the exposed and susceptible individuals, including the reduction of the between-group contact, would be an effective approach to protect the most vulnerable people in this population group.


Asunto(s)
COVID-19 , Simulación por Computador , Humanos , Modelos Teóricos , Prevalencia , SARS-CoV-2
14.
BMJ Open ; 11(7): e048874, 2021 07 02.
Artículo en Inglés | MEDLINE | ID: mdl-34215611

RESUMEN

OBJECTIVES: To investigate the impact of targeted vaccination strategies on morbidity and mortality due to COVID-19, as well as on the incidence of SARS-CoV-2, in India. DESIGN: Mathematical modelling. SETTINGS: Indian epidemic of COVID-19 and vulnerable population. DATA SOURCES: Country-specific and age-segregated pattern of social contact, case fatality rate and demographic data obtained from peer-reviewed literature and public domain. MODEL: An age-structured dynamical model describing SARS-CoV-2 transmission in India incorporating uncertainty in natural history parameters was constructed. INTERVENTIONS: Comparison of different vaccine strategies by targeting priority groups such as keyworkers including healthcare professionals, individuals with comorbidities (24-60 years old) and all above 60. MAIN OUTCOME MEASURES: Incidence reduction and averted deaths in different scenarios, assuming that the current restrictions are fully lifted as vaccination is implemented. RESULTS: The priority groups together account for about 18% of India's population. An infection-preventing vaccine with 60% efficacy covering all these groups would reduce peak symptomatic incidence by 20.6% (95% uncertainty intervals (UI) 16.7-25.4) and cumulative mortality by 29.7% (95% CrI 25.8-33.8). A similar vaccine with ability to prevent symptoms (but not infection) will reduce peak incidence of symptomatic cases by 10.4% (95% CrI 8.4-13.0) and cumulative mortality by 32.9% (95% CrI 28.6-37.3). In the event of insufficient vaccine supply to cover all priority groups, model projections suggest that after keyworkers, vaccine strategy should prioritise all who are >60 and subsequently individuals with comorbidities. In settings with weakest transmission, such as sparsely populated rural areas, those with comorbidities should be prioritised after keyworkers. CONCLUSIONS: An appropriately targeted vaccination strategy would witness substantial mitigation of impact of COVID-19 in a country like India with wide heterogeneity. 'Smart vaccination', based on public health considerations, rather than mass vaccination, appears prudent.


Asunto(s)
COVID-19 , Adulto , Humanos , India/epidemiología , Persona de Mediana Edad , Modelos Teóricos , SARS-CoV-2 , Vacunación , Adulto Joven
15.
Math Biosci Eng ; 18(4): 3384-3403, 2021 04 15.
Artículo en Inglés | MEDLINE | ID: mdl-34198391

RESUMEN

Lockdown and social distancing, as well as testing and contact tracing, are the main measures assumed by the governments to control and limit the spread of COVID-19 infection. In reason of that, special attention was recently paid by the scientific community to the mathematical modeling of infection spreading by including in classical models the effects of the distribution of contacts between individuals. Among other approaches, the coupling of the classical SIR model with a statistical study of the distribution of social contacts among the population, led some of the present authors to build a Social SIR model, able to accurately follow the effect of the decrease in contacts resulting from the lockdown measures adopted in various European countries in the first phase of the epidemic. The Social SIR has been recently tested and improved through a fruitful collaboration with the Health Protection Agency (ATS) of the province of Pavia (Italy), that made it possible to have at disposal all the relevant data relative to the spreading of COVID-19 infection in the province (half a million of people), starting from February 2020. The statistical analysis of the data was relevant to fit at best the parameters of the mathematical model, and to make short-term predictions of the spreading evolution in order to optimize the response of the local health system.


Asunto(s)
COVID-19 , Epidemias , Control de Enfermedades Transmisibles , Europa (Continente) , Humanos , Italia , Modelos Teóricos , SARS-CoV-2
16.
Artículo en Inglés | MEDLINE | ID: mdl-34199937

RESUMEN

Time-variant positive air pressure in a drainage stack poses a risk of pathogenic virus transmission into a habitable space, however, the excessive risk and its significance have not yet been sufficiently addressed for drainage system designs. This study proposes a novel measure for the probable pathogenic virus transmission risk of a high-rise drainage stack with the occurrence of positive air pressure. The proposed approach is based on time-variant positive air pressures measured in a 38 m high drainage stack of a full-scale experimental tower under steady flow conditions of flow rate 1-4 Ls-1 discharging at a height between 15 m to 33 m above the stack base. The maximum pressure and probabilistic positive air pressures in the discharging stack ventilation section with no water (Zone A of the discharging drainage stack) were determined. It was demonstrated that the positive air pressures were lower in frequency as compared with those in other stack zones and could propagate along the upper 1/3 portion of the ventilation pipe (H' ≥ 0.63) towards the ventilation opening at the rooftop. As the probabilistic positive pressures at a stack height were found to be related to the water discharging height and flow rate, a risk model of positive air pressure is proposed. Taking the 119th, 124th, 140th and 11,547th COVID-19 cases of an epidemiological investigation in Hong Kong as a baseline of concern, excessive risk of system overuse was evaluated. The results showed that for a 20-80% increase in the frequency of discharge flow rate, the number of floors identified at risk increased from 1 to 9 and 1 to 6 in the 34- and 25-storey residential buildings, respectively. The outcome can apply to facilities planning for self-quarantine arrangements in high-rise buildings where pathogenic virus transmission associated with drainage system overuse is a concern.


Asunto(s)
COVID-19 , Presión del Aire , Hong Kong , Humanos , Modelos Teóricos , SARS-CoV-2
17.
Artículo en Inglés | MEDLINE | ID: mdl-34201285

RESUMEN

A novel statistical model based on a two-layer, contact and information, graph is suggested in order to study the influence of disease prevalence on voluntary general population vaccination during the COVID-19 outbreak. Details about the structure and number of susceptible, infectious, and recovered/vaccinated individuals from the contact layer are simultaneously transferred to the information layer. The ever-growing wealth of information that is becoming available about the COVID virus was modelled at each individual level by a simplified proxy predictor of the amount of disease spread. Each informed individual, a node in a heterogeneous graph, makes a decision about vaccination "motivated" by their benefit. The obtained results showed that disease information type, global or local, has a significant impact on an individual vaccination decision. A number of different scenarios were investigated. The scenarios showed that in the case of the stronger impact of globally broadcasted disease information, individuals tend to vaccinate in larger numbers at the same time when the infection has already spread within the population. If individuals make vaccination decisions based on locally available information, the vaccination rate is uniformly spread during infection outbreak duration. Prioritising elderly population vaccination leads to an increased number of infected cases and a higher reduction in mortality. The developed model accuracy allows the precise targeting of vaccination order depending on the individuals' number of social contacts. Precisely targeted vaccination, combined with pre-existing immunity, and public health measures can limit the infection to isolated hotspots inside the population, as well as significantly delay and lower the infection peak.


Asunto(s)
COVID-19 , Anciano , Brotes de Enfermedades/prevención & control , Humanos , Modelos Teóricos , Prevalencia , SARS-CoV-2 , Vacunación
18.
Int J Mol Sci ; 22(13)2021 Jun 22.
Artículo en Inglés | MEDLINE | ID: mdl-34206440

RESUMEN

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) are increasingly being shown to play major roles in cellular self-organization dynamics in health and disease. It is well established that macromolecular crowding has a profound impact on protein interactions, particularly those that lead to LLPS. Although synthetic crowding agents are used during in vitro LLPS experiments, they are considerably different from the highly crowded nucleo-/cytoplasm and the effects of in vivo crowding remain poorly understood. In this work, we applied computational modeling to investigate the effects of macromolecular crowding on LLPS. To include biologically relevant LLPS dynamics, we extended the conventional Cahn-Hilliard model for phase separation by coupling it to experimentally derived macromolecular crowding dynamics and state-dependent reaction kinetics. Through extensive field-theoretic computer simulations, we show that the inclusion of macromolecular crowding results in late-stage coarsening and the stabilization of relatively smaller condensates. At a high crowding concentration, there is an accelerated growth and late-stage arrest of droplet formation, effectively resulting in anomalous labyrinthine morphologies akin to protein gelation observed in experiments. These results not only elucidate the crowder effects observed in experiments, but also highlight the importance of including state-dependent kinetics in LLPS models, and may help in designing further experiments to probe the intricate roles played by LLPS in self-organization dynamics of cells.


Asunto(s)
Extracción Líquido-Líquido/métodos , Sustancias Macromoleculares/química , Sustancias Macromoleculares/aislamiento & purificación , Algoritmos , Humanos , Cinética , Modelos Teóricos
19.
Int J Mol Sci ; 22(13)2021 Jun 22.
Artículo en Inglés | MEDLINE | ID: mdl-34206572

RESUMEN

Lipophilicity of 15 derivatives of sodium cholate, defined by the octan-1-ol/water partition coefficient (log P), has been theoretically determined by the Virtual log P method. These derivatives bear highly hydrophobic or highly hydrophilic substituents at the C3 position of the steroid nucleus, being linked to it through an amide bond. The difference between the maximum value of log P and the minimum one is enlarged to 3.5. The partition coefficient and the critical micelle concentration (cmc) are tightly related by a double-logarithm relationship (VirtuallogP=-(1.00±0.09)log(cmcmM)+(2.79±0.09)), meaning that the Gibbs free energies for the transfer of a bile anion from water to either a micelle or to octan-1-ol differ by a constant. The equation also means that cmc can be used as a measurement of lipophilicity. The demicellization of the aggregates formed by three derivatives of sodium cholate bearing bulky hydrophobic substituents has been studied by surface tension and isothermal titration calorimetry. Aggregation numbers, enthalpies, free energies, entropies, and heat capacities, ΔCP,demic, were obtained. ΔCP,demic, being positive, means that the interior of the aggregates is hydrophobic.


Asunto(s)
Ácidos y Sales Biliares/química , Interacciones Hidrofóbicas e Hidrofílicas , Algoritmos , Calorimetría , Fenómenos Químicos , Micelas , Modelos Teóricos , Estructura Molecular , Termodinámica
20.
Int J Mol Sci ; 22(12)2021 Jun 20.
Artículo en Inglés | MEDLINE | ID: mdl-34202954

RESUMEN

Backgroud: The prediction of drug-target interactions (DTIs) is of great significance in drug development. It is time-consuming and expensive in traditional experimental methods. Machine learning can reduce the cost of prediction and is limited by the characteristics of imbalanced datasets and problems of essential feature selection. METHODS: The prediction method based on the Ensemble model of Multiple Feature Pairs (Ensemble-MFP) is introduced. Firstly, three negative sets are generated according to the Euclidean distance of three feature pairs. Then, the negative samples of the validation set/test set are randomly selected from the union set of the three negative sets in the validation set/test set. At the same time, the ensemble model with weight is optimized and applied to the test set. RESULTS: The area under the receiver operating characteristic curve (area under ROC, AUC) in three out of four sub-datasets in gold standard datasets was more than 94.0% in the prediction of new drugs. The effectiveness of the proposed method is also shown with the comparison of state-of-the-art methods and demonstration of predicted drug-target pairs. CONCLUSION: The Ensemble-MFP can weigh the existing feature pairs and has a good prediction effect for general prediction on new drugs.


Asunto(s)
Algoritmos , Desarrollo de Medicamentos/métodos , Modelos Teóricos , Área Bajo la Curva , Desarrollo de Medicamentos/normas , Aprendizaje Automático , Reproducibilidad de los Resultados , Máquina de Vectores de Soporte
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