Traditional Chinese Medicine Syndromes in Depressive Episodes of Bipolar Disorder Based on Cluster Analysis and Bayesian Network：A Cross-sectional Study / 中医杂志

ObjectiveTo explore the elements， distribution and characteristics of traditional Chinese medicine （TCM） syndromes in depressive episodes of bipolar disorder （BD）. MethodsBasic information， along with the four examination information， the Hamilton Depression Scale and Young Mania Rating Scale scores， were collected from 293 outpatients with BD at Beijing Anding Hospital， Capital Medical University. The four examination information with an occurrence rate greater than 12% were retained. The R language “dist” function was used to calculate the distances between samples using the Euclidean distance method. The hierarchical clustering of the four examination information was performed using the “hclust” function and the squared Euclidean distance method. A team of five researchers was formed to determine the nature and location of the essential elements of TCM syndrome in BD based on the clustering results. The PC algorithm was used to construct a Bayesian network model of the essential elements. The working group combined the essential elements of TCM syndromes in the Bayesian network according to the reference model results， and then extracted common TCM syndromes. The score of each patient based on the essential elements was matched with the common TCM syndromes to determine the syndrome type of each patient. The working group then performs conformity and revision based on this， obtaining the final distribution of TCM syndromes for the patients. ResultsThere were 77 common TCM symptoms in BD with a frequency greater than 12%. The top 15 symptoms with higher frequencies were slippery pulse， mental fatigue and lack of strength， wiry pulse， excessive rumination， preference for solitude， vexation， agitation and irritability， dry mouth， palpitations， profuse dreaming， unwarranted worries， chest oppression， thin white coating， amnesia， frequent sighing， and poor appetite. TCM syndrome elements of BD can be grouped into 11 categories. The nature of disease-related essential elements included fire， qi deficiency， blood deficiency， qi counterflow， yin deficiency， dampness， heat， fire from constraint， and phlegm. The location of disease-related essential elements included heart， liver， spleen， stomach， kidney， bladder channel， and gallbladder. By constructing a Bayesian network model and considering the opinions from the experts， six common syndromes of BD were identified， among which the highest proportion was heart-stomach heat accumulation， accounting for 27.99% （82 cases）， followed by heart-spleen deficiency （55 cases， 18.77%）， non-interaction between the heart and the kidney （49 cases， 16.72%）， liver constraint and blood deficiency （42 cases， 14.33%）， heart qi deficiency （37 cases， 12.63%）， and damp-heat in the liver and gallbladder （28 cases， 9.56%）. ConclusionsThe nature of disease-related elements of BD are predominantly fire and heat， while the location of disease-related essential elements are primarily associated with the heart， liver， and spleen. The most common TCM syndromes are heart-stomach heat accumulation and heart-spleen deficiency.

Nonparametric item response models: a comparison on recovering true scores / Modelos de resposta ao item não-paramétricos: comparando a recuperação de escores verdadeiros / Modelos de respuesta al item no-paramétricos: comparando la recuperación de puntuaciones verdaderas

Nonparametric procedures are used to add flexibility to models. Three nonparametric item response models have been proposed, but not directly compared: the Kernel smoothing (KS-IRT); the Davidian-Curve (DC-IRT); and the Bayesian semiparametric Rasch model (SP-Rasch). The main aim of the present study is to compare the performance of these procedures in recovering simulated true scores, using sum scores as benchmarks. The secondary aim is to compare their performances in terms of practical equivalence with real data. Overall, the results show that, apart from the DC-IRT, which is the model that performs the worse, all the other models give results quite similar to those when sum scores are used. These results are followed by a discussion with practical implications and recommendations for future studies.(AU)

Procedimentos não paramétricos são usados para adicionar flexibilidade aos modelos. Três modelos não paramétricos de resposta ao item foram propostos, mas não comparados diretamente: o Kernel smoothing (KS-IRT); a Curva Davidiana (DC-IRT); e o modelo semiparamétrico Rasch Bayesiano (SP-Rasch). O objetivo principal do presente estudo é comparar o desempenho desses procedimentos na recuperação de escores verdadeiros simulados, utilizando escores de soma como benchmarks. O objetivo secundário é comparar seus desempenhos em termos de equivalência prática com dados reais. De forma geral, os resultados mostram que, além do DC-IRT, que é o modelo que apresenta o pior desempenho, todos os outros modelos apresentam resultados bastante semelhantes aos de quando se usam somatórios. Esses resultados são seguidos de uma discussão com implicações práticas e recomendações para estudos futuros.(AU)

Se utilizan procedimientos no paramétricos para agregar flexibilidad a los modelos. Se propusieron tres modelos de respuesta al ítem no paramétricos, pero no se compararon directamente: Kernel smoothing (KS-IRT); la curva davidiana (DC-IRT); y el modelo bayesiano de Rasch semiparamétrico (SP-Rasch). El objetivo principal del presente estudio es comparar el desempeño de estos procedimientos en la recuperación de puntajes verdaderos simulados, utilizando puntajes de suma como puntos de referencia. El objetivo secundario es comparar su desempeño en términos de equivalencia práctica con datos reales. En general, los resultados muestran que, a excepción de DC-IRT, que es el modelo con peor desempeño, todos los otros modelos presentan resultados bastante similares a los obtenidos cuando se utilizan sumatorios. Estos resultados son seguidos por una discusión con implicaciones prácticas y recomendaciones para estudios futuros.(AU)

Challenges and Perspectives in Target Identification and Mechanism Illustration for Chinese Medicine / 中国结合医学杂志

Chinese medicine (CM) is an important resource for human life understanding and discovery of drugs. However, due to the unclear pharmacological mechanism caused by unclear target, research and international promotion of many active components have made little progress in the past decades of years. CM is mainly composed of multi-ingredients with multi-targets. The identification of targets of multiple active components and the weight analysis of multiple targets in a specific pathological environment, that is, the determination of the most important target is the main obstacle to the mechanism clarification and thus hinders its internationalization. In this review, the main approach to target identification and network pharmacology were summarized. And BIBm (Bayesian inference modeling), a powerful method for drug target identification and key pathway determination was introduced. We aim to provide a new scientific basis and ideas for the development and international promotion of new drugs based on CM.

Research on mild cognitive impairment diagnosis based on Bayesian optimized long-short-term neural network model / 生物医学工程学杂志

The recurrent neural network architecture improves the processing ability of time-series data. However, issues such as exploding gradients and poor feature extraction limit its application in the automatic diagnosis of mild cognitive impairment (MCI). This paper proposed a research approach for building an MCI diagnostic model using a Bayesian-optimized bidirectional long short-term memory network (BO-BiLSTM) to address this problem. The diagnostic model was based on a Bayesian algorithm and combined prior distribution and posterior probability results to optimize the BO-BiLSTM network hyperparameters. It also used multiple feature quantities that fully reflected the cognitive state of the MCI brain, such as power spectral density, fuzzy entropy, and multifractal spectrum, as the input of the diagnostic model to achieve automatic MCI diagnosis. The results showed that the feature-fused Bayesian-optimized BiLSTM network model achieved an MCI diagnostic accuracy of 98.64% and effectively completed the diagnostic assessment of MCI. In conclusion, based on this optimization, the long short-term neural network model has achieved automatic diagnostic assessment of MCI, providing a new diagnostic model for intelligent diagnosis of MCI.

Lean strategy for data mining and continuous improvement of Chinese pharmaceutical process: a case study of sporoderm-removal Ganoderma lucidum spore powder / 中国中药杂志

In the digital transformation of Chinese pharmaceutical industry, how to efficiently govern and analyze industrial data and excavate the valuable information contained therein to guide the production of drug products has always been a research hotspot and application difficulty. Generally, the Chinese pharmaceutical technique is relatively extensive, and the consistency of drug quality needs to be improved. To address this problem, we proposed an optimization method combining advanced calculation tools(e.g., Bayesian network, convolutional neural network, and Pareto multi-objective optimization algorithm) with lean six sigma tools(e.g., Shewhart control chart and process performance index) to dig deeply into historical industrial data and guide the continuous improvement of pharmaceutical processes. Further, we employed this strategy to optimize the manufacturing process of sporoderm-removal Ganoderma lucidum spore powder. After optimization, we preliminarily obtained the possible interval combination of critical parameters to ensure the P_(pk) values of the critical quality properties including moisture, fineness, crude polysaccharide, and total triterpenes of the sporoderm-removal G. lucidum spore powder to be no less than 1.33. The results indicate that the proposed strategy has an industrial application value.

Network Meta-analysis of Chinese patent medicine containing Hirudo in treatment of atherosclerosis / 中国中药杂志

This study aimed to evaluate the efficacy and safety of Chinese patent medicines containing Hirudo in the treatment of atherosclerosis(AS) by network Meta-analysis, and to provide evidence-based reference for clinical treatment of AS. The clinical randomized controlled trial(RCT) on the treatment of atherosclerosis with Chinese patent medicines containing Hirudo were searched in CNKI, Wanfang, VIP, SinoMed, PubMed and EMbase from the establishment of the databases to July 1, 2022. And data extraction and quality assessment of the included RCT was performed according to the Cochrane standards. Stata 17 and ADDIS 1.16.5 were then used for Bayesian model network Meta-analysis. Finally, 67 RCTs with a total sample size of 6 826 cases were included, 3 569 cases in the experimental group and 3 257 cases in the control group, involving three oral Chinese patent medicines. Network Meta-analysis showed that in terms of reducing intima-media thickness(IMT), the top three Chinese patent medicines were Tongxinluo Capsules+sta-tins>Maixuekang Capsules+statins>Maixuekang Capsules. In terms of reducing plaque area, the top one was Maixuekang Capsules+sta-tins, and the other Chinese patent medicines had similar efficacy. For lowering AS Crouse scores, the top three were Maixuekang Capsules>Tongxinluo Capsules+statins>Naoxintong Capsules. For decreasing plaque number, the top three were Naoxintong Capsules+sta-tins>Tongxinluo Capsules+statins>Tongxinluo Capsules. With regard to adverse reactions/events, Naoxintong Capsules+statins had the lo-west incidence. In conclusion, in Chinese patent medicines containing Hirudo for the treatment of AS, Tongxinluo Capsules+statins, Maixuekang Capsules, Maixuekang Capsules+statins, and Naoxintong Capsules+statins were the primary choices to reduce IMT, AS Crouse scores, plaque area, and plaque number, respectively. The efficacy of Chinese patent medicines containing Hirudo with or without statins was more significant than that of statins alone in the four outcome indexes. Additionally, the treatment of AS should be evaluated comprehensively, and attention should be paid to Chinese patent medicines or their combination with western medicine, to optimize the treatment effect and minimize adverse reactions as the benchmark.

Modelo bayesiano de series temporales estructurales. Aproximación a la evaluación de impacto de VA-MENGOC-BC®

Introducción: Una nueva intervención de salud pública, como la introducción de una vacuna, implica el monitoreo de indicadores que aseguren una intervención efectiva, y que exista la posibilidad de cuantificar sus beneficios. Obtener estimaciones precisas del impacto de una intervención de salud se considera un desafío importante. Objetivos: Estimar el impacto causal de uno de los productos líderes del Instituto Finlay de La Habana: la vacuna cubana registrada y comercializada VA-MENGOC-BC®. Métodos: Se seleccionaron datos en los anuarios estadísticos de salud desde 2009 hasta 2017. Se usaron como variable de interés, la tasa de incidencia de la enfermedad meningocócica en Cuba ( 100 000 habitantes y un conjunto de covariables que no se afectaron por la intervención: tasas de incidencia de fiebre tifoidea, de incidencia de tuberculosis, de mortalidad por enfermedades infecciosas (parasitarias e intestinales) todas ( 100 000 habitantes. Se consideró 1989 como año de la intervención. Se aplicó el método bayesiano de series temporales estructurales, que evaluó el impacto causal de la vacunación sostenida con VA-MENGOC-BC® desde 1989 hasta el presente. Resultados: Se estimó un impacto causal acumulativo significativo en la reducción de la incidencia de la enfermedad meningocócica. Se verificó que se produjo una disminución de la enfermedad en 97,2 %. Conclusiones: La aplicación del método de series de tiempo estructural bayesina para estimar el impacto de la vacuna VA-MENGOC-BC®, constituyó una herramienta novedosa para evaluar el contrafactual. Se proporcionó una apreciación del impacto de la vacunación con VA-MENGOC-BC®, una vacuna implementada y reconocida a nivel mundial.

Introduction: A new public health intervention, such as the introduction of a vaccine, implies monitoring the indicators that guarantee its effectiveness, and the possibility of quantifying its benefits. Obtaining accurate estimates of the impact of a health intervention is considered a major challenge. Objective: To estimate the causal impact of one of the leading products of the Finlay Institute in Havana: the registered and marketed Cuban vaccine VA-MENGOC-BC®. Methods: Data from the health statistics yearbooks from 2009 to 2017 were selected. The incidence rate of the meningococcal disease in Cuba per 100 000 population and a set of co-variables that were not affected by the intervention, such as incidence rate of typhoid fever, tuberculosis, and fatality cases due to infectious diseases (parasitic or intestinal) per 100 000 population were used as variables of interest. The intervention year was 1989. The Bayesian structural time series model was applied to evaluate the causal impact of the continued vaccination with VA-MENGOC-BC® from 1989 to date. Results: A significant cumulative causal impact in reducing the incidence of meningococcal disease was estimated. A decrease of 97.2% in the disease was verified. Conclusions: The application of the Bayesian structural time series model to estimate the impact of the vaccine VA-MENGOC-BC® was a novel tool to estimate the counterfactual. It was provided an estimate of the impact of the vaccination with VA-MENGOC-BC®, an implemented and globally well-known vaccine.

Associations between urinary paraben levels and obesity of 10-year-old children / 环境与职业医学

Background Parabens, a widely used class of preservatives, are suspected to be potential obesogens as emerging endocrine disrupting chemicals with reproductive and developmental toxicity. Objective To analyze five urinary parabens (PBs) and estimate the associations of exposure to PBs with adiposity measures in 10-year-old school-age children. Methods A total of 471 school-age children aged 10 years from the Sheyang Mini Birth Cohort were enrolled in this study. A questionnaire survey was conducted to collect socio-demographic information, physical activity, and dietary intake. Weight, height, and waist circumference of children were measured, and age- and sex-adjusted body mass index (BMI-Z score) was calculated. Spot urine samples were collected during the follow-up visits. Urinary concentrations of five PBs including methyl-paraben (MeP), ethyl-paraben (EtP), propyl-paraben (PrP), butyl-paraben (BuP), and benzyl-paraben (BzP) were detected by gas chromatography-tandem mass spectrometry (GC-MS/MS). Generalized linear models (GLMs) and Bayesian kernel machine regression (BKMR) models were applied to estimate associations of individual/overall urinary PBs concentrations with BMI Z-score and waist circumference. Results The positive rates of selected five urinary PBs were in the range from 78.98% to 98.94%. The urinary PBs concentrations (geometric mean) were in the range of 0.31-5.43 μg·L−1. The children's BMI Z-score and waist circumference (mean ± standard deviation) were (0.56±1.40) and (67.62±10.07) cm respectively. The GLMs results showed that the urinary BzP concentration was negatively associated with waist circumference (b=−0.08, 95%CI: −0.14, −0.02; P=0.01). In sex-stratified analysis, the urinary concentration of BzP was negatively associated with BMI-Z score (b=−0.59, 95%CI: −0.88, −0.30; P<0.001) and waist circumference (b=−0.80, 95%CI: −1.23, −0.37; P<0.001) in boys, but not in girls. The BKMR results also found significant negative correlations of urinary BzP concentrations with BMI-Z score and waist circumference, which were consistent with the GLM results. Conclusion The selected 10-year-old children are extensively exposed to PBs in the study area. Furthermore, childhood PBs exposure may have potential impacts on childhood adiposity measures with sex-specific effects.

Influencing factors of fall injury risks in manufacturing enterprises based on Bayesian networks / 环境与职业医学

Background Falls are one of the most important types of occupational injuries. The incidence of falls is high in manufacturing workers. However, most of the studies on falls in China focus on primary and secondary school students and the elderly, and there are few studies on falls in the occupational population. Objective To evaluate efficiency of Bayesian network model in predicting fall injury risks in manufacturing enterprise staff, and impacts from work content, work environment, enterprise status, and health management on falls and their mutual relationships, and provide a scientific basis for enterprises to carry out fall-associated injury intervention. Methods Data from the European Survey of Enterprises on New and Emerging Risks (ESENER) were used. The survey provided data on work content, working environment, enterprise status, and health management of enterprises in European countries. The outcome indicator, was fall injury risks reported in enterprises. A total of 23 potential impact factors covering work content, working environment, enterprise status, and health management were screened by least absolute shrinkage and selection operator (LASSO) regression, followed by Bayesian network model for structure learning and parameter learning and area under the curve (AUC) for model fitness evaluation, using R and Netica 5.18. Diagnostic inference analysis was also conducted to identify key influencing factors and key influencing chains of fall injury risks based on the change rate of fall injury risks. Results In 5997 enterprises surveyed, 2573 (42.9%) enterprises reported fall injury risks. Ordered by their coefficient estimates from high to low, the 14 variables (mean-squared error=0.20) selected by LASSO regression were: manual handling, repetitive arm movement, poor posture, using desktop computers, and using robots in the category of work content; abnormal temperature and noise in the category of working environment; company size and employee quality in the category of enterprise status; mental health training, regular risk assessment, availability of psychologists, health and safety procedures, and provision of psychological counseling in the category of health management. The fitting result of Bayesian network model for fall injury risks was good (AUC=0.779). The Bayesian network diagnostic inference identified five key influencing factors, including abnormal temperature (change rate=35.9%), poor posture (change rate=27.3%), noise (change rate=23.4%), manual handling (change rate=18.2%), and repetitive arm movement (change rate=5.1%). The key influencing chain was "manual handling - poor posture - repetitive arm movement - fall injury risks" (combined change rate=16.9%). Conclusion The Bayesian network model has a good predictive performance in predicting the risk of falls in manufacturing enterprises. Manufacturing enterprises need to focus on jobs involving manual handling and repetitive arm movement, identify and improve workers' poor posture and mental health problems, and avoid workers working in harsh temperature or noise environment.

Relationship between mixed exposure to heavy metals and seminal fructose in men of childbearing age / 环境与职业医学

Background The human body is usually exposed to a variety of heavy metals at the same time, and different types and concentrations of heavy metals may have complex interactions during their absorption and metabolism in the human body. Seminal fructose is an important energy source for sperm movement. A large number of studies have shown that metal exposure may impair semen quality, and seminal fructose is an important factor affecting male reproduction, so it is necessary to investigate the relationship between mixed heavy metal exposure and seminal fructose to explore the mechanism of semen quality damage caused by metal exposure. Objective To understand the status of common heavy metal exposure in men of childbearing age in Puyang City, Henan Province, and to study the relationship between mixed exposure to heavy metals and seminal fructose, as well as potential interactions among heavy metals. Methods Volunteers were recruited from the Puyang Maternal and Child Health Hospital Reproductive Center for a cross-sectional survey on general demographic characteristics, smoking, alcohol consumption, and other information. Semen samples were collected to detect 12 metals such as vanadium (V), manganese (Mn), cobalt (Co), nickel (Ni), zinc (Zn), selenium (Se), silver (Ag), cadmium (Cd), barium (Ba), thallium (Tl), iron (Fe), and lead (Pb) in seminal plasma and seminal fructose. After correcting for selected confounding factors, a Bayesian kernel machine regression (BKMR) model was used to evaluate the impact of seminal plasma heavy metal mixed exposure and its interactions on seminal fructose. Results A total of 825 adult males were enrolled. The concentrations in M (P25, P75) of V, Mn, Co, Ni, Zn, Se, Ag, Cd, Ba, Tl, Fe, and Pb in seminal plasma were 0.39 (0.28, 0.54), 12.31 (8.92, 17.52), 0.26 (0.18, 0.38), 5.15 (3.32, 8.64), 182159.80 (121847.80, 199144.50), 13.61 (10.55, 17.68), 0.03 (0.02, 0.04), 0.34 (0.27, 0.46), 8.64 (5.94, 13.43), 0.06 (0.05, 0.08), 168.74 (114.17, 259.45), and 1.69 (1.15, 2.36) μg·L−1 respectively. The Spearman correlation results indicated that there was a negative correlation between V, Mn, Co, Zn, Se, Ba, Tl, or Fe in seminal plasma and seminal fructose (P<0.05), and the values of r (95%CI) were −0.044 (−0.087, −0.001), −0.129 (−0.171, −0.087), −0.055 (−0.099, −0.012), −0.099 (−0.143, −0.056), −0.053 (−0.097, −0.010), −0.068 (−0.111, −0.025), −0.095 (−0.138, −0.052), and −0.082 (−0.125, −0.039), respectively. The results of multiple linear regression indicated that there was a negative correlation between the exposure level of Cd, Mn, Zn, Ag, Ba, Tl, or Fe in seminal plasma and seminal fructose (P<0.05), the values of associated β (95%CI) were −0.551 (−0.956, −0.147), −0.315 (−0.419, −0.212), −0.187 (−0.272, −0.103), −0.161 (−0.301, −0.021), −0.188 (−0.314, −0.062), −1.159 (−2.170, −0.147), and −0.153 (−0.230, −0.076), respectively. The BKMR model analysis showed that seminal fructose level decreased with the increase of plasma metal mixed exposure concentration. Compared with all metal exposure at P50, the seminal fructose level decreased by 0.2374 units when all metal exposure was at P75. Seminal plasma Zn [posterior inclusion probabilities (PIPs)=1.0000] had the strongest effect on seminal fructose, followed by Mn (PIPs=0.5872), Se (PIPs=0.5656), and Ba (PIPs=0.5398). The univariate exposure-response curve showed a negative approximate linear correlations between Ba or Mn and seminal fructose, a positive linear correlation between Se and seminal fructose, and an approximate inverted U-shaped association between Zn and seminal fructose. No significant interaction between studied metals was found. Conclusion Mixed metal exposure may lead to decrease of seminal fructose, in which Zn, Mn, Se, and Ba may play an important role. Mn and Zn exposure may reduce the level of seminal fructose, Se may increase the level of seminal fructose, and there may be a threshold effect between Zn exposure and seminal fructose level. No interaction between different metals on seminal fructose is found.

Bayesian Network Meta-analysis of Therapeutic Effect of Oral Chinese Patent Medicines on Coronary Artery Disease Complicated with Carotid Atherosclerosis / 中国实验方剂学杂志

ObjectiveTo compare the therapeutic effects of oral Chinese medicines （including Chinese patent medicines） on coronary artery disease （CAD） by the Bayesian network Meta-analysis. MethodThe randomized controlled trials of treating CAD with oral Chinese medicines were retrieved from the China National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP， PubMed， Web of Science， Embase， and Cochrane Library from the inception to December 1， 2022. The Cochrane risk of bias assessment tool was used to evaluate the quality of the included articles. The direct meta-analysis was performed to compare the performance of oral Chinese medicines alone and in combination with Western medicine in the treatment of CAD in terms of intima-media thickness （IMT）， vascular endothelial function， plaque score， hypersensitive C-reactive protein （hs-CRP）， total cholesterol （TC）， triglyceride （TG）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， and total response rate. Furthermore， the Bayesian network Meta-analysis was performed to compare the therapeutic effects of different Chinese medicines. ResultA total of 41 articles were included. The direct meta-analysis results showed that Chinese medicines combined with Western medicine outperformed Western medicine alone in recovering all the indicators of CAD. The Bayesian network meta-analysis yielded the following results. In terms of the total response rate， modified Huangqi Guizhi Wuwutang and Sanqi Huayu pills had obvious advantages over other Chinese medicines. In terms of IMT and plaque score， Xiaoban Huazhuo decoction， Yiqi Tongluo formula， Ruangan Jiangzhi capsules， and Guanxin Shutong capsules had obvious advantages over other Chinese medicines. In terms of blood lipid indicators， Shenqi Roumai mixture， Ruangan Jiangzhi capsules， Xiaoban Huazhuo decoction， Qiwei Sanxiong decoction， and Sanqi Huayu pills were superior to other Chinese medicines. The Chinese medicines above mainly had the functions of activating blood， resolving stasis， resolving phlegm， and dredging vessels. ConclusionThe combination of oral Chinese medicines and Western medicine is effective in treating CAD. Clinicians can use the drugs targeting abnormal indicators according to the results of this Bayesian network meta-analysis combined with the actual situation of patients to achieve better therapeutic effects.

Evaluación de los retrasos en actividades de construcción utilizando redes Bayesianas: Caso de estudio / Delay assessment of construction site activities using Bayesian networks: Case study / Avaliação dos atrasos nas atividades de construção utilizando redes Bayesianas: Estudo de caso

RESUMEN Los retrasos en proyectos de construcción son atribuídos a la concurrencia de factores que afectan el buen desarrollo, y mitigarlos, constituye uno de los mayores desafios que afronta la industria, ya que requiere tener en cuenta la dependencia e incidencia integrada de ellos. El objetivo de este estudio fue evaluar la influencia de factores de retraso sobre la duración de actividades de construcción, a través de un método que emplee las redes Bayesianas. Siguiendo la metodologia de investigación basada en el diseno, y aplicando un caso de estudio, se propone un método que incluye cómo identificar los principales factores de retraso que afecten las actividades; cómo representar la influencia y dependencia de estos factores por medio de una red Bayesiana; y cómo estimar el nivel de influencia por medio de la simulación de la red. Los resultados de esta investigación muestran como la aplicación de una red Bayesiana se puede emplear como apoyo a los profesionales de obra para gestionar las actividades de construcción y tomar decisiones en la medida que se actualice la información de la red bayesiana.

ABSTRACT The concurrence of multiple factors adversely affects construction project performance, resulting in delays. Mitigating such factors is challenging for the industry because solutions must include dependence and influence. Hence, managers must consider their systemic and integrated influence on the construction process for tracking projects. This study aimed to evaluate the influence of delay factors on the duration of construction site activities using Bayesian network techniques. Based on the design-based research methodology and the application in a case study this study proposed a method that involves three steps. First, identifying the main delay factors affecting construction activities; second, designing an influencing model as a Bayesian network; and third, estimating the integrated influence of such factors by simulating the Bayesian network. The results showed how a Bayesian network could support the construction team in managing the construction-site activities and making decisions about the performance of the construction process.

RESUMO Atrasos nos projetos de construção são atribuídos à concorrência de múltiplos fatores que afetam o desenvolvimento adequado do projeto, e mitigá-los é um dos maiores desafios enfrentados pelo setor; pois requer levar em conta a incidência integrada dos mesmos. O objetivo deste estudo foi avaliar a influência de um grupo de fatores sobre a duração das atividades de construção, utilizando a técnica da rede Bayesiana. Seguindo a metodologia de pesquisa baseada em projeto, foram identificados os principais fatores de atraso que afetam as atividades de construção e as relações de causa e efeito foram modeladas para estimar sua influência sobre a duração das atividades de fundação de um projeto de construção. Os resultados desta pesquisa mostram como a aplicação de uma rede Bayesiana pode ser usada para apoiar os profissionais do local no gerenciamento das atividades de construção e na tomada de decisões relativas ao desenvolvimento do projeto, considerando a incerteza e os fatores que influenciam o desenvolvimento do projeto.

Bayesian threshold analysis of litter size in sheep

Background: Litter size at birth (LSB) is one of the most important economic traits in sheep and could be used in genetic improvement schemes for meat production. LSB is inherently a categorical trait and should be analysed with threshold models. Objective: Bayesian threshold models were used to analyze sheep LSB to estimate genetic parameters. Methods: Data was based on 7,901 LSB records from 14,968 dams and 682 sires collected from 1986 to 2012 at Makouie Sheep Breeding Station in Iran. Means of posterior distributions (MPDs) of LSB's genetic parameters were estimated, and the best-fitted models were selected using the deviance information criterion. Results: In the repeated measurement analysis, the estimated direct and maternal heritabilities, and permanent environmental effect (±SE), according to the best-fitted model (model 5), were 0.01 (0.010), 0.02 (0.014), and 0.01 (0.011), respectively. In the univariate analysis, the best estimates of direct and maternal heritabilities were 0.12 (0.064) and 0.08 (0.045), respectively. An increasing trend for direct and maternal heritabilities was observed in parity 2 (0.15 (0.082) and 0.25 (0.083), respectively). In the bivariate analysis, the best estimates of direct and maternal heritabilities for LSB were 0.03 (0.027) and 0.22 (0.041), respectively. The direct and maternal genetic correlations among parities were 0.25 (0.054) and 0.12 (0.021), respectively. Conclusions: The results showed a considerable influence of environmental factors on LSB in each parity of sheep; also, statistically different genetic parameters (p<0.05) were obtained from one parity to another, indicating the different and large influences of genetic and environmental factors for each parity.

Antecedentes: El tamaño de la camada al nacer (LSB) es inherentemente un rasgo categórico y debe analizarse con modelos de umbral. El LSB es uno de los rasgos de producción de carne más importantes en las ovejas y podría usarse en esquemas de mejora genética para la producción de carne. Objetivo: Se utilizaron modelos de umbral bayesiano para analizar el tamaño de la camada de ovejas al nacer (LSB) y estimar parámetros genéticos. Métodos: Los datos se basaron en 7.901 registros de LSB de 14.968 ovejas y 682 carneros recolectados de 1986 a 2012 en la estación de cría de ovejas Makouie en Irán. Se estimaron las medias de distribuciones posteriores (MPD) de los parámetros genéticos de LSB y se seleccionaron los modelos mejor ajustados utilizando el criterio de información de desviación. Resultados: En los análisis de medición repetida, la heredabilidad materna y directa estimada y el efecto ambiental permanente (±SE), según el modelo mejor ajustado (modelo 5), fueron 0,01 (0,010), 0,02 (0,014) y 0,01 (0,011), respectivamente. En el análisis univariado, las mejores estimaciones de heredabilidad directa y materna fueron 0,12 (0,064) y 0,08 (0,045), respectivamente. Se observó una tendencia creciente de heredabilidades directas y maternas en la paridad 2 (0,15 (0,082) y 0,25 (0,083), respectivamente). En el análisis bivariado, las mejores estimaciones de heredabilidad directa y materna para LSB fueron 0,03 (0,027) y 0,22 (0,041), respectivamente. Las correlaciones genéticas directas y maternas entre partos fueron 0,25 (0,054) y 0,12 (0,021), respectivamente. Conclusiones: Los resultados mostraron una influencia considerable de los factores ambientales sobre el LSB en cada parto de las ovejas; además, se obtuvieron parámetros genéticos estadísticamente diferentes (p<0.05) de un parto a otro, indicando las diferentes y grandes influencias de factores genéticos y ambientales para cada parto en ovejas. Los resultados de este estudio se pueden precisar aún más utilizando datos de SNP de todo el genoma sobre diferentes partes para manejar una amplia gama de problemas relacionados con la interacción del entorno genético del rasgo LSB.

Antecedentes: O tamanho da ninhada ao nascer (LSB) é inerentemente uma característica categórica e deve ser analisada com modelos de limiar. LSB é uma das características mais importantes de produção de carne em ovinos e pode ser usado em esquemas de melhoramento genético para a produção de carne. Objetivo: Modelos de limiar bayesiano foram usados para analisar o tamanho da ninhada de ovelhas ao nascer (LSB) para estimar parâmetros genéticos. Métodos: Os dados foram baseados em 7.901 registros LSB de 14.968 ovelhas e 682 carneiros coletados de 1986 a 2012 na Estação de Criação de Ovinos Makouie no Irã. Médias de distribuições posteriores (MPDs) dos parâmetros genéticos de LSB foram estimadas e os modelos mais bem ajustados foram selecionados usando o critério de informação de desvio. Resultados: Nas análises de medidas repetidas, as herdabilidades diretas e maternas estimadas e o efeito do ambiente permanente (±SE), de acordo com o modelo mais bem ajustado (modelo 5), foram 0,01 (0,010), 0,02 (0,014) e 0,01 (0,011), respectivamente. Na análise univariada, as melhores estimativas das herdabilidades direta e materna foram 0,12 (0,064) e 0,08 (0,045), respectivamente. Uma tendência crescente para as herdabilidades direta e materna foi observada na paridade 2 (0,15 (0,082) e 0,25 (0,083), respectivamente). Na análise bivariada, as melhores estimativas de herdabilidades direta e materna para LSB foram 0,03 (0,027) e 0,22 (0,041), respectivamente. As correlações genéticas diretas e maternas entre os partos foram 0,25 (0,054) e 0,12 (0,021), respectivamente. Conclusões: Os resultados mostraram uma influência considerável dos fatores ambientais na LSB em cada paridade de ovelhas; também, parâmetros genéticos estatisticamente diferentes (p<0,05) foram obtidos de uma paridade para outra, indicando as diferentes e grandes influências de fatores genéticos e ambientais para cada paridade em ovinos. Os resultados deste estudo podem ser ainda mais definidos usando dados SNPs de todo o genoma em diferentes partes para lidar com uma ampla gama de problemas relacionados à interação do ambiente genético do traço LSB.

El Enfoque Bayesiano en las Ciencias de la Salud / The Bayesian Approach in the Health Sciences

En estadística existen dos enfoques básicos, la estadística frecuentista que es la corriente principal y la estadística bayesiana. La mayoría de los principales métodos estadísticos son frecuentistas siendo el enfoque bayesiano más desconocido entre los investigadores. En el presente artículo se exponen los fundamentos lógicos del enfoque bayesiano y su uso mediante un ejemplo de aplicación. En este contexto, más que presentar un debate entre la lógica clásica y la bayesiana, se pretende mostrar de manera introductoria las enormes posibilidades que el enfoque bayesiano puede aportar a la investigación en las Ciencias de la Salud.

In the stadistic field there are two basic approaches, the Frequentist Statistics which is the primary one, and the Bayesian Statistics. The most used statistical methods are the Frequentist methods, being the Bayesian approach the most popular among researchers. In this article, the logical basis of the Bayendian approach and its use are exposed through an application example. In this context, rather than presenting a debate between the classic and the Bayensian logic, it is intended to demonstrate in an introductory method the considerable possibilities how Bayesian approach can contribute to Health and Sciences research.

Application of bayesian network in nursing real-world data and implementation of tetrad / 中国实用护理杂志

Objective:It introduced the application of bayesian network in real-world data and the implementation of Tetrad software, so as to provide methodological application reference for medical researchers.Methods:Real-world data for diabetes diagnosis had been taken as an example. UCI machine learning database Pima-Indian-diabetes data set was used as case data, Bayesian network ratiocination was carried out according to the construction order of bayesian network of Tetrad software.Results:When the screening age was over 30 years old, impaired glucose tolerance, abnormal serum insulin two hours after meal, body weight index and family genetic index were large, the probability of diabetes onset from 34.99% to 83.33%.Conclusions:The bayesian network realized by Tetrad software provides a powerful tool for causal inference of real-world data, and promoted the objective and quantitative interpretation of the dependence between variables.

Benchmark dose estimation based on Bayesian model averaging and its application to evaluation of cadmium exposure of population in Baiyin / 环境与职业医学

Background The optimal model method for estimation of benchmark dose (BMD) does not consider the uncertainty of model selection. There is a lack of studies on using Bayesian model averaging (BMA) to estimate BMD. Objective To apply BMA to the exposure assessment of cadmium pollution in China, discuss the role of BMA in estimating BMD based on dose-response models, and to provide methodological support for health risk assessment of hazardous substances. Methods The parameters of five dose-response models (Gamma, Log-logistic, Log-probit, Two-stage, and Weibull models) estimated from the data from a cadmium-contaminated area in Baiyin City of Gansu Province and the urinary cadmium ranges in five cadmium-contaminated areas in China were used to simulate the data of varied correct models with different numbers of dosage groups (5 and 8) and different sample sizes (50, 100, and 200), then the performance of BMA and traditional optimal model were compared. The case analysis used the cadmium exposure data in Baiyin, Gansu Province. All analyses set urinary cadmium as the indicator of cadmium exposure, the abnormal rate of β2-microglobulin as the effect indicator, and the benchmark response to 10%. The correct model (the model used when simulating data), optimal model [the model with smallest Akaike information criterion (AIC)], and BMA were used to estimate BMD and lower confidence limit of benchmark dose (BMDL); the BMDs, BMDLs, and relative deviations from different methods were compared. Results In the simulation study, with increasing sample size or the number of dosage groups, the intervals of the 5th percentile and the 90th percentile of BMD tended to be narrower; when the correct model was a single model, the relative deviation of BMD estimation by BMA was greater than that of the traditional optimal model; when the correct model was an equal weight mixed model, the relative deviation of BMD estimation by BMA was less than that by the traditional optimal model. For the data of cadmium-contaminated areas, the optimal model was a Log-probit model (AIC=1814.46), followed by a Log-logistic model (AIC=1814.57); the BMDs (BMDLs) estimated by the Log-probit model, the Log-logistic model, and BMA were 3.46 (2.68), 3.16 (2.33), and 2.92 (2.07) μg·g−1, respectively. Conclusion The traditional optimal model is still recommended when the correct model is known. However, when the dose-response relationship of a hazardous substance is uncertain or with different sources or exposure grouping, compared with the traditional optimal model, BMA theoretically provides more stable estimation of BMD and BMDL by considering multiple possible alternative models.

Application of three statistical models in association between polycyclic aromatic hydrocarbons exposure and cognitive level in workers / 环境与职业医学

Background As a complex organic pollutant, polycyclic aromatic hydrocarbons (PAHs) exposure shares the common exposure characteristics of multiple hydroxyl metabolites. Most studies have analyzed independent effect of each PAHs metabolite and have adjusted for the potential confounding effects induced by other metabolites concomitantly, without considering possible interactions among them. Proper statistical methods are needed to study their toxic effects. Objective To explore the applicability of logistic regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) in evaluating the correlation between mixed exposures to exogenous chemicals and health outcomes, compare the advantages and limitations of the three models, and propose analytical strategies for evaluating the health effects of mixed chemical exposure for application in the analysis of the association between PAHs exposure and cognition. Methods Urine samples were collected of workers from a coke oven plant and a water treatment plant in Shanxi Province, who participated in their routine employee healthexamination. Mono-hydroxylated PAHs were detected by high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS), cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). A cut-off value of MoCA less than 26 was considered mild cognitive impairment (MCI). According to a predetermined inclusion and exclusion criteria, 1 051 cases were included in the final data analysis. Logistic regression, WQS regression, and BKMR were used to analyze the relationship between PAHs metabolites and MCI. Results The prevalence rate of reporting MCI among the 1 051 workers was 21.7% (228/1 051). The concentration of 2-hydroxynathalene (2-OHNAP) was the highest among the 11 PAHs metabolites with a median concentration of 0.30 μg·L−1, followed by 9-hydroxyphenanthrene (9-OHPHE) (0.26 μg·L−1). There were significant differences between the two groups in 2-OHNAP, 1-hydroxynaphthalene (1-OHNAP), 2-hydroxyfluorene (2-OHFLU), 9-OHPHE, 1-hydroxyphenanthrene (1-OHPHE), and 1-hydroxypyrene (1-OHPYR) (all Ps<0.05). In the logistic regression, 2-OHNAP and 2-OHPHE were associated with MCI, and the OR (95%CI) for reporting MCI was 1.28 (1.01-1.67) and 1.27 (1.00-1.72) for each 10-fold increase in 2-OHNAP and 2-OHPHE concentrations, respectively. In the WQS regression analysis, the WQS index was positively correlated with the prevalence rate of reporting MCI (OR=1.37, 95%CI: 1.10-1.72). In the BKMR analysis, compared with the median exposure levels of all chemicals, the overall effect was statistically significant when all PAHs metabolites concentrations were at or above their 30th percentile; when all exposures were at the 75th percentile, the risk of reporting MCI increased by 6%. Conclusion Based on the results of these three models, 2-OHNAP and 2-OHPHE are the most important factors related to cognitive. It is recommended to use a combination of traditional logistic regression and either WQS or BKMR to study the association between PAHs and MCI.

Relationship between heatwave and years of life lost associated with stroke in Guangdong Province: Based on Bayesian spatio-temporal model / 环境与职业医学

Background Stroke has become a main cause of death in China. With global warming, the studies on temperature and stroke have attracted much attention. Objective To analyze he relationships between heatwave and the years of life lost (YLL) by different subtypes of stroke by controlling temporal and spatial effects with Bayesian spatio-temporal model, and to study the modifiers of the health effect of heatwave. Methods The daily information of stroke deaths, meteorological data, and air pollutant data in 40 districts and counties of Guangdong Province were collected during the warm seasons (from May to October) in the years from 2014 to 2017. The individual YLL was first calculated by matching age and gender according to the life table, and then the daily YLL rate (person-years/100 000 people) was obtained by summarizing the daily YLL and correcting it with the population of each district or county. Bayesian spatio-temporal model was used to fit a proposed exposure-response relationship between heatwave and the YLL rates of different subtypes of stroke. Finally, stratified analyses were conducted by age (<65 years, ≥65 years), gender (male, female), and region (Pearl River Delta and non-Pearl River Delta regions) to identify the major modifiers for the association between heatwave and stroke mortality. Results During the warm seasons from 2014 to 2017, a total of 23 heatwave events occurred in the 40 districts or counties of Guangdong Province, cumulatively lasting for 145 d. A total of 30 852 stroke deaths were recorded in the same time periods. The average daily YLL rate of total stroke was (2.39±3.63) person-years/100 000 people, and those for hemorrhagic stroke and ischemic stroke were (1.54±2.99) person-years/100 000 people and (0.84±1.85) person-years/100 000 people, respectively. Heatwave was associated with increased YLL rate of stroke in residents, and it had a greater impact on ischemic stroke with a lag effect. The largest cumulative effect of heatwave was at lag 0-1 day, which was associated with an increased YLL rate of total stroke and ischemic stroke by 0.17 (95%CI: 0.03-0.29) person-years/100 000 people and 0.13 (95%CI: 0.06-0.20) person-years/100 000 people, respectively. The results of stratified analyses showed that heatwave had a larger effect on ischemic stroke in residents of aged 65 years or older, male, and non-Pearl River Delta regions, and the rates of YLL increased by 1.11 (95%CI: 0.58-1.55), 0.13 (95%CI: 0.03-0.23), and 0.20 (95%CI: 0.07-0.32) person-years/100 000 people, respectively; Heatwave only had an effect on hemorrhagic stroke in residents aged 65 years or older with an increased YLL rate of 0.79 (95%CI: 0.26-1.31) person-years/100 000 people. Conclusion Heatwave could elevate the level of years of life lost associated with stroke in Guangdong residents, with greater impacts on ischemic stroke of the aged, men, and residents in non-Pearl River Delta regions, and on hemorrhagic stroke in the elderly.

Socio-economic status as predictors of malaria transmission in KwaZulu-Natal, South Africa. A retrospective study

Background: Understanding the socioeconomic status that influences malaria transmission in KwaZulu-Natal, South Africa is vital in creating policies and strategies to combat malaria transmission, improve socioeconomic conditions and strengthen the malaria elimination campaign. Objectives: To determine the relationship between socioeconomic status and malaria incidence in KwaZulu-Natal, South Africa. Methods: Socioeconomic information (gender, age, no formal education, no electricity, no toilet facilities, unemployment) and malaria data for 2011 were obtained from Statistics South Africa and the malaria control program of KwaZulu-Natal, South Africa respectively. The analysis was conducted employing the Bayesian multiple regression model. Results: The obtained posterior samples show that all the variables employed in this study were significant and positive predictors of malaria disease at 95% credible interval. The low socioeconomic status that exhibited the strongest association with malaria risk was lack of toilet facilities (odd ratio =12.39; 95% credible interval = 0.61, 24.36). This was followed by no formal education (odd ratio =11.11; 95% credible interval = 0.51, 24.10) and lack of electricity supply (odd ratio =8.94; 95% credible interval = 0.31, 23.21) respectively. Conclusions: Low socioeconomic status potentially sustains malaria transmission and burden. As an implication, poverty alleviation and malaria intervention resources should be incorporated side by side into the socioeconomic framework to attain zero malaria transmission.

Phylogenetic relationships of the supercontig of sodium channel subunit I (NaV) in 17 species of Anopheles (Diptera: Culicidae)

ABSTRACT Background: Malaria is a global health problem and is transmitted by the Anopheles species. Due to the epidemiological importance of the genus, studies on biological, phylogenetic, and evolutionary aspects have contributed to the understanding of adaptation, vector capacity, and resistance to insecticides. The latter may result from different causes such as mutations in the gene that encodes the sodium channel (NaV). Methods: In this study, the NaV subunit I scaffold of 17 anopheline species was used to infer phylogenetic relationships of the genus Anopheles using Bayesian inference. The evolutionary phylogenetic tree of the NaV gene was aligned in the AliView program and analyzed utilizing Bayesian inference, using the software MrBayes. Results: The anophelines were grouped into five well-supported clusters: 1 - Anopheles darlingi and Anopheles albimanus; 2 - Anopheles sinensis and Anopheles atroparvus; 3 - Anopheles dirus; 4 - Anopheles minimus, Anopheles culicifacies, Anopheles funestus, Anopheles maculatus, and Anopheles stephensi; and 5 - Anopheles christyi, Anopheles epiroticus, Anopheles merus, Anopheles melas, Anopheles gambiae, Anopheles coluzzii, and Anopheles arabiensis. Conclusions: The topology confirms the phylogenetic relationships proposed in studies based on the genome of some anophelines and reflects the current taxonomy of the genus, which suggests that NaV undergoes selection pressure during the evolution of the species. These data are useful tools for inferring their ability to resist insecticides and also help in better understanding the evolutionary processes of the genus Anopheles.