No abstract

Spatiotemporal analysis is an important tool to monitor changes of tuberculosis (TB) epidemiology, identify high-risk regions and guide resource allocation. However, there are limited data on the contributing factors of TB incidence. This study aimed to investigate the spatiotemporal pattern of TB incidence and its associated factors in mainland China during 2005-2013. Global Moran's I test, Getis-Ord Gi index and heat maps were used to examine the spatial clustering and seasonal patterns. Generalized Linear Mixed Model was applied to identify factors associated with TB incidence. TB incidence presented high geographical variations with two main hot spots, while a generally consistent seasonal pattern was observed with a peak in late winter. Furthermore, we found province-level TB incidence increased with the proportion of the elderly but decreased with Gross Demographic Product per capita and the male:female ratio. Meteorological factors also influenced TB incidence. TB showed obvious spatial clustering in mainland China and both the demographic and socio-economic factors and meteorological measures were associated with TB incidence. These results provide the related information to identify the high-risk districts and the evidence for the government to develop corresponding control measures.

In order to transport materials flexibly and smoothly in a tight plant environment, an omni-directional mobile robot based on four Mecanum wheels was designed. The mechanical system of the mobile robot is made up of three separable layers so as to simplify its combination and reorganization. Each modularized wheel was installed on a vertical suspension mechanism, which ensures the moving stability and keeps the distances of four wheels invariable. The control system consists of two-level controllers that implement motion control and multi-sensor data processing, respectively. In order to make the mobile robot navigate in an unknown semi-structured indoor environment, the data from a Kinect visual sensor and four wheel encoders were fused to localize the mobile robot using an extended Kalman filter with specific processing. Finally, the mobile robot was integrated in an intelligent manufacturing system for material conveying. Experimental results show that the omni-directional mobile robot can move stably and autonomously in an indoor environment and in industrial fields.

Granulomatous lobular mastitis (GLM) is a rare and chronic benign inflammatory disease of the breast. Difficulties exist in the management of GLM for many front-line surgeons and medical specialists who care for patients with inflammatory disorders of the breast. This consensus is summarized to establish evidence-based recommendations for the management of GLM. Literature was reviewed using PubMed from January 1, 1971 to July 31, 2020. Sixty-six international experienced multidisciplinary experts from 11 countries or regions were invited to review the evidence. Levels of evidence were determined using the American College of Physicians grading system, and recommendations were discussed until consensus. Experts discussed and concluded 30 recommendations on historical definitions, etiology and predisposing factors, diagnosis criteria, treatment, clinical stages, relapse and recurrence of GLM. GLM was recommended as a widely accepted definition. In addition, this consensus introduced a new clinical stages and management algorithm for GLM to provide individual treatment strategies. In conclusion, diagnosis of GLM depends on a combination of history, clinical manifestations, imaging examinations, laboratory examinations and pathology. The approach to treatment of GLM should be applied according to the different clinical stage of GLM. This evidence-based consensus would be valuable to assist front-line surgeons and medical specialists in the optimal management of GLM.

Due to the lack of an accurate preoperative diagnostic method of central lymph node metastasis (CLNM) of papillary thyroid cancer (PTC), the prophylaxis of central lymph node dissection remains controversial. The present study investigated the clinicopathological features of PTC patients and the risk factors of CLNM. The clinicopathological features of PTC patients with respect to sex, age, initial symptoms, observation, tumor diameter, multifocality, extrathyroidal invasion, and pathological data combined with other thyroid diseases, were analyzed retrospectively. The risk factors of CLNM were analyzed by Chi-squared test and multivariate logistic regression model. The CLNM rate of PTC was 40.6% (1331/3273). On average, 7.0 (4.0, 12.0) central lymph nodes were dissected, and 3.70 (±3.8) lymph nodes were proved to be metastatic. Univariate analysis showed that sex (P < .001), age (P < .001), tumor diameter (P < .001), extrathyroid invasion (P < .001), multifocality (P = .001), concurrent nodular goiter (P < .001), initial symptoms (P < .001), and observation or not (P < .001) were related to CLNM. The observation time was neither related to CLNM (P = .469) nor extrathyroidal invasion (P = .137). Tumors localized in the lower part of the thyroid were the risk factors for CLNM (P < .001) while multifocality was unrelated (P = .68). The metastasis rate of bilateral multiple regions > unilateral multiple regions > single region (P = .003). Multivariate logistic regression analysis showed that sex, age, tumor diameter, extrathyroidal invasion, and observation were independent risk factors of CLNM. Male, younger age, large tumor size, and extrathyroidal invasion were independent risk factors for CLNM. CLNM was related to multiple regions occupied by tumors in the thyroid but unrelated to multifocality. The tumor occupying a single region and localized in the lower part of thyroid could be used as a predictive factor for CLNM. For tumors that could not be diagnosed as benign or malignant, observation may be an option, since no evidence of disease progression was presented during observation.

BackgroundThe temporal variation of malaria incidence has been linked to meteorological factors in many studies, but key factors observed and corresponding effect estimates were not consistent. Furthermore, the potential effect modification by individual characteristics is not well documented. This study intends to examine the delayed effects of meteorological factors and the sub-population’s susceptibility in Guangdong, China.MethodsThe Granger causality Wald test and Spearman correlation analysis were employed to select climatic variables influencing malaria. The distributed lag non-linear model (DLNM) was used to estimate the non-linear and delayed effects of weekly temperature, duration of sunshine, and precipitation on the weekly number of malaria cases after controlling for other confounders. Stratified analyses were conducted to identify the sub-population’s susceptibility to meteorological effects by malaria type, gender, and age group.ResultsAn incidence rate of 1.1 cases per 1,000,000 people was detected in Guangdong from 2005–2013. High temperature was associated with an observed increase in malaria incidence, with the effect lasting for four weeks and a maximum relative risk (RR) of 1.57 (95% confidence interval (CI): 1.06-2.33) by comparing 30°C to the median temperature. The effect of sunshine duration peaked at lag five and the maximum RR was 1.36 (95% CI: 1.08-1.72) by comparing 24 hours/week to 0 hours/week. A J-shaped relationship was found between malaria incidence and precipitation with a threshold of 150 mm/week. Over the threshold, precipitation increased malaria incidence after four weeks with the effect lasting for 15 weeks, and the maximum RR of 1.55 (95% CI: 1.18-2.03) occurring at lag eight by comparing 225 mm/week to 0 mm/week. Plasmodium falciparum was more sensitive to temperature and precipitation than Plasmodium vivax. Females had a higher susceptibility to the effects of sunshine and precipitation, and children and the elderly were more sensitive to the change of temperature, sunshine duration, and precipitation.ConclusionTemperature, duration of sunshine and precipitation played important roles in malaria incidence with effects delayed and varied across lags. Climatic effects were distinct among sub-groups. This study provided helpful information for predicting malaria incidence and developing the future warning system.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-015-0630-6) contains supplementary material, which is available to authorized users.

Early preoperative diagnosis of central lymph node metastasis (CNM) is crucial to improve survival rates among patients with papillary thyroid carcinoma (PTC). Here, we analyzed clinical data from 2862 PTC patients and developed a scoring system using multivariable logistic regression and testified by the validation group. The predictive diagnostic effectiveness of the scoring system was evaluated based on consistency, discrimination ability, and accuracy. The scoring system considered seven variables: gender, age, tumor size, microcalcification, resistance index >0.7, multiple nodular lesions, and extrathyroid extension. The area under the receiver operating characteristic curve (AUC) was 0.742, indicating a good discrimination. Using 5 points as a diagnostic threshold, the validation results for validation group had an AUC of 0.758, indicating good discrimination and consistency in the scoring system. The sensitivity of this predictive model for preoperative diagnosis of CNM was 4 times higher than a direct ultrasound diagnosis. These data indicate that the CNM prediction model would improve preoperative diagnostic sensitivity for CNM in patients with papillary thyroid carcinoma.

Background New coronavirus disease 2019 (COVID-19) has posed a severe threat to human life and caused a global pandemic. The current research aimed to explore whether the search-engine query patterns could serve as a potential tool for monitoring the outbreak of COVID-19. Methods We collected the number of COVID-19 confirmed cases between January 11, 2020, and April 22, 2020, from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). The search index values of the most common symptoms of COVID-19 (e.g., fever, cough, fatigue) were retrieved from the Baidu Index. Spearman’s correlation analysis was used to analyze the association between the Baidu index values for each COVID-19-related symptom and the number of confirmed cases. Regional distributions among 34 provinces/ regions in China were also analyzed. Results Daily growth of confirmed cases and Baidu index values for each COVID-19-related symptom presented robust positive correlations during the outbreak (fever: rs=0.705, p=9.623× 10− 6; cough: rs=0.592, p=4.485× 10− 4; fatigue: rs=0.629, p=1.494× 10− 4; sputum production: rs=0.648, p=8.206× 10− 5; shortness of breath: rs=0.656, p=6.182× 10–5). The average search-to-confirmed interval (STCI) was 19.8 days in China. The daily Baidu Index value’s optimal time lags were the 4 days for cough, 2 days for fatigue, 3 days for sputum production, 1 day for shortness of breath, and 0 days for fever. Conclusion The searches of COVID-19-related symptoms on the Baidu search engine were significantly correlated to the number of confirmed cases. Since the Baidu search engine could reflect the public’s attention to the pandemic and the regional epidemics of viruses, relevant departments need to pay more attention to areas with high searches of COVID-19-related symptoms and take precautionary measures to prevent these potentially infected persons from further spreading.