This study aimed to estimate the attack rates, and identify the risk factors of COVID-19 infection. Based on a retrospective cohort study, we investigated 11,580 contacts of COVID-19 cases in Guangdong Province from 10 January to 15 March 2020. All contacts were tested by RT-PCR to detect their infection of SARS-COV-2. Attack rates by characteristics were calculated. Logistic regression was used to estimate the risk factors of infection for COVID-19. A total of 515 of...

This study aimed to estimate the attack rates, and identify the risk factors of COVID-19 infection. Based on a retrospective cohort study, we investigated 11,580 contacts of COVID-19 cases in Guangdong Province from 10 January to 15 March 2020. All contacts were tested by RT-PCR to detect their infection of SARS-COV-2. Attack rates by characteristics were calculated. Logistic regression was used to estimate the risk factors of infection for COVID-19. A total of 515 of...

A dynamic treatment regime (DTR) is a sequence of decision rules that adapt to the time-varying states of an individual. Black-box learning methods have shown great potential in predicting the optimal treatments; however, the resulting DTRs lack interpretability, which is of paramount importance for medical experts to understand and implement. We present a stochastic tree-based reinforcement learning (ST-RL) method for estimating optimal DTRs in a multistage multitreatment setting with data from either randomized trials or...

A dynamic treatment regime (DTR) is a sequence of decision rules that adapt to the time-varying states of an individual. Black-box learning methods have shown great potential in predicting the optimal treatments; however, the resulting DTRs lack interpretability, which is of paramount importance for medical experts to understand and implement. We present a stochastic tree-based reinforcement learning (ST-RL) method for estimating optimal DTRs in a multistage multitreatment setting with data from either randomized trials or...

Ovarian cancer stem cells (OCSCs) that are a subpopulation within bulk tumor survive chemotherapy and conduce to chemo-resistance and tumor relapse. However, conventional gene delivery is unsuitable for the on-demand content release, which limits OCSCs therapeutic utility. Here, we reported ultrasound-targeted microbubble destruction (UTMD)-triggerable poly(ethylene glycol)-disulfide bond-polyethylenimine loaded microbubble (PSP@MB). Taking advantage of glutathione (GSH) responsiveness, ultrasound triggering and spatiotemporally controlled release manner, PSP@MB is expected to realize local gene delivery for OCSCs treatment. But...

Ovarian cancer stem cells (OCSCs) that are a subpopulation within bulk tumor survive chemotherapy and conduce to chemo-resistance and tumor relapse. However, conventional gene delivery is unsuitable for the on-demand content release, which limits OCSCs therapeutic utility. Here, we reported ultrasound-targeted microbubble destruction (UTMD)-triggerable poly(ethylene glycol)-disulfide bond-polyethylenimine loaded microbubble (PSP@MB). Taking advantage of glutathione (GSH) responsiveness, ultrasound triggering and spatiotemporally controlled release manner, PSP@MB is expected to realize local gene delivery for OCSCs treatment. But...