Machine learning and statistical models for analyzing multilevel patent data.

A recent surge of patent applications among public hospitals in China has aroused significant research interest. A country's healthcare innovation capacity can be measured by its number of patents. This paper explores the link between the number of patents and ten independent variables. Multicollinearity was carefully detected and removed by using the variable selection method and LASSO regression, respectively. The Poisson model and the negative binomial model were proposed to analyze the patent data. Three goodness of fit tests, the Pearson test, the deviance test, and the DHARMa non-parametric dispersion test, were conducted to investigate if the model has a good fit. After discovering four clusters by conducting agglomerative hierarchical clustering, these two models were replaced by the negative binomial mixed model. The likelihood ratio test was used to determine which model is more appropriate and the results reveal that the negative binomial mixed model outperforms both the Poisson model and the negative binomial model. Three variables, number of health technicians per 10,000 people, financial expenditure on science and technology as well as number of patent applications per 10,000 health personnel, have a significantly positive relationship with the number of patents in Chinese tertiary public hospitals.

A Self-Priming Digital Polymerase Chain Reaction Chip for Multiplex Genetic Analysis.

Digital PCR (polymerase chain reaction) is a powerful and attractive tool for the quantification of nucleic acids. However, the multiplex detection capabilities of this system are limited or require expensive instrumentation and reagents, all of which can hinder multiplex detection goals. Here, we propose strategies toward solving these issues regarding digital PCR. We designed and tested a self-priming digital PCR chip containing 6-plex detection capabilities using monochrome fluorescence, which has six detection areas and four-layer structures. This strategy achieved multiplex digital detection by the use of self-priming to preintroduce the specific reaction mix to a certain detection area. This avoids competition when multiple primer pairs coexist, allowing for multiplexing in a shorter time while using less reagents and low-cost instruments. This also prevents the digital PCR chip from experiencing long sample introduction time and evaporation. For further validation, this multiplex digital PCR chip was used to detect five types of EGFR (epidermal growth factor receptor) gene mutations in 15 blood samples from lung cancer patients. We conclude that this technique can precisely quantify EGFR mutations in high-performance diagnostics. This multiplex digital detection chip is a simple and inexpensive test intended for liquid biopsies. It can be applied and used in prenatal diagnostics, the monitoring of residual disease, rapid pathogen detection, and many other procedures.

Rapid In Situ Photoimmobilization of a Planar Droplet Array for Digital PCR.

Digital PCR (dPCR) is a powerful technique capable of absolute quantification of nucleic acids with good accuracy. Droplet-based dPCR (ddPCR), among others, is one of the most important dPCR techniques. However, the surface tension-controlled droplets may suffer from fusion/fission due to the vigorous temperature change in PCR thermal cycling. Besides, the free movement of droplets makes them unsuitable for real-time fluorescence monitoring. In this paper, we first developed a photoimmobilized planar droplet array (PIPDA) by using a photocurable polyurethane as the continuous oil phase. It is found that uniform water-in-oil droplets of various sizes can be readily generated, and more importantly, the oil phase can be rapidly solidified in just a few seconds upon exposure to UV irradiation. This process will leave the droplets immobilized in the accommodation chamber as a stable planar array and, thus, effectively prevent the movement, coalescence, and breakup of droplets. In addition, a novel multilayered chip design has been proposed, which can thoroughly overcome the evaporation issue that commonly exists in polydimethylsiloxane (PDMS)-based dPCR chips. With these two innovations, the ddPCR experiment could be performed in a robust manner, and shows a promising potential in the development of real-time ddPCR technique. These features may therefore enable the wide application of PIPDA-based ddPCR in various fields.