A Dataset on Population Activity Patterns in Typical Regions of North China.

This data article describes the "Typical Regional Activity Patterns" (TRAP) dataset, which is based on the Tackling Key Problems in Air Pollution Control Program. In order to explore the interaction between air pollution and physical activity, we collected activity patterns of 9,221 residents with different occupations and lifestyles for three consecutive days in typical regions (Jinan and Baoding) where air pollutant concentrations were higher than those in neighboring areas. The TRAP dataset consists of two aspects of information: demographic indicators (personal information, occupation, personal habits, and living situation) and physical activity pattern data (activity location and intensity); additionally, the exposure measures of physical activity patterns are included, which data users can match to various endpoints for their specific purpose. This dataset provides evidence for exploring the attributes of activity patterns of residents in northern China and for interdisciplinary researchers to develop strategies and measures for health education and health promotion.

Immunogenicity of a spike protein subunit-based COVID-19 vaccine with broad protection against various SARS-CoV-2 variants in animal studies.

SARS-CoV-2 pandemic has profound impacts on human life and global economy since the outbreak in 2019. With the new variants continue to emerge with greater immune escaping capability, the protectivity of the available vaccines is compromised. Therefore, development a vaccine that is capable of inducing immunity against variants including omicron strains is in urgent need. In this study, we developed a protein-based vaccine BCVax that is consisted of antigen delta strain spike protein and QS21-based adjuvant AB801 in nanoparticle immune stimulation complex format (AB801-ISCOM). Results from animal studies showed that high level of anti-S protein IgG was induced after two doses of BCVax and the IgG was capable of neutralizing multiple variants of pseudovirus including omicron BA.1 or BA.2 strains. In addition, strong Th1 response was stimulated after BCVax immunization. Furthermore, BCvax with AB801-ISCOM as the adjuvant showed significant stronger immunity compared with the vaccine using aluminum hydroxide plus CpG 1018 as the adjuvant. BCVax was also evaluated as a booster after two prior vaccinations, the IgG titers and pseudovirus neutralization activities against BA.2 or BA.4/BA.5 were further enhanced suggesting BCVax is a promising candidate as booster. Taken together, the pre-clinical data warrant BCVax for further development in clinic.

Detection of Dental Apical Lesions Using CNNs on Periapical Radiograph.

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion.

Effect of profit status in facilities on the mortality of patients on long-term haemodialysis: a nationwide cohort study.

OBJECTIVES: Over the past two decades, debates on whether the profit status of dialysis facilities influences patient prognosis have been popular in the USA. Taiwan is one of the regions with the highest rate per capita of kidney replacement therapy worldwide, but no similar research has been conducted to date. This is the first study to address this issue. DESIGN: This was a nationwide retrospective cohort study based on the Taiwan Renal Registry Data System. SETTING: Patients were categorised into two groups based on the profit status (for-profit, not-for-profit (NFP)) of dialysis facilities, with 31 350 patients in each group. The patients were followed up from 2005 to 2012. PARTICIPANTS: Patients with uraemia who underwent long-term haemodialysis in private dialysis facilities and public facilities were excluded. PRIMARY AND SECONDARY OUTCOME MEASURES: Survival analyses were performed to compare prognosis between the two groups. Adjustments to patients' basic profile, and facilities' geographical distribution, level, and length of ownership were carried out to minimise possible confounding effects. RESULTS: Analysis revealed that NFP dialysis facilities had better outcomes (HR=0.91, 95% CI (0.89 to 0.93)). A favourable effect remains with the adjustment of the facilities' level, geographical distribution (HR=0.89, 95% CI (0.86 to 0.93)) or length of ownership (HR=0.95, 95% CI (0.89 to 0.95)). Survival analysis based on the geographical distribution and level of facilities was also conducted, which showed better prognosis in medical centres in the six municipalities, whereas worse prognosis was found in local hospitals not located in these municipalities. CONCLUSION: Our findings suggest that in contemporary settings in Taiwan, treatment at NFP dialysis facilities was associated with a better prognosis. The results should be interpreted with caution since the possibility of residual confounding effects and uncertainty of casual relations exist due to the nature of observational studies.

Caries and Restoration Detection Using Bitewing Film Based on Transfer Learning with CNNs.

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early, the treatment will be relatively easy, which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However, the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu's threshold image enhancement technology, this research solves the problem that the original cutting technology cannot extract certain single teeth, and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN), which can identify caries and restorations from the bitewing images. Moreover, it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image, which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization, (2) a dental image cropping procedure to obtain individually separated tooth samples, and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks, namely, AlexNet, GoogleNet, Vgg19, and ResNet50, experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%, respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film.

Adsorption intrinsic kinetics and isotherms of lead ions on steel slag.

Batch experiments were carried out to investigate the kinetics of adsorption of lead ions by steel slag on the basis of the external diffusion, intra-particle diffusion and adsorption reaction model (pseudo-first-order, pseudo-second-order). The results showed that the controlling step for the adsorption kinetics changed with the varying experimental parameters. When the particle size of steel slag was larger than 120 mesh, intra-particle diffusion of Pb(2+) was the controlling step, and when the initial concentration of Pb(2+) was less than 150 m gL(-1) or the shaking rate was lower than 150 rpm, external diffusion of Pb(2+) was promoted. Contrary to the former experimental conditions the adsorption reaction was the controlling step, and the adsorption followed second-order kinetics, with an adsorption rate constant of 13.26 g mg(-1)min(-1). The adsorption isotherm of Pb(2+) with steel slag followed the Langmuir model, with a correlation coefficient of 0.99.

Kinetic models for the adsorption of lead ions by steel slag.

Batch experiments were carried out to investigate the kinetics of adsorption of lead ions by steel slag on the basis of the external diffusion, intraparticle diffusion and adsorption reaction model (pseudo-first-order, pseudo-second-order). The results showed that the controlling step for the adsorption kinetics changed with experimental parameters varied. When the particle size of steel slag was larger than 120 mesh, intraparticle diffusion of Pb(2+) was the controlling step; when the initial concentration of Pb(2+) was less than 150 mg L(-1) or the shaking rate was lower than 150 rpm, external diffusion of Pb(2+) was promoted. Contrary to the former experimental conditions, the adsorption reaction was the controlling step, and the adsorption followed second-order kinetics, with an adsorption rate constant of 13.26 g mg(-1) min(- 1). The adsorption isotherm of Pb(2+) with steel slag followed the Langmuir model, with a correlation coefficient of 0.99.