Noncovalent Indocyanine Green Conjugate of C-Phycocyanin: Preparation and Tumor-Associated Macrophages-Targeted Photothermal Therapeutics.

Fabrication of a multifunctional near-infrared (NIR) theranostic nanoplatform has attracted increasing attention. Indocyanine green (ICG), a clinic-approved NIR fluorescence-imaging agent, is an excellent photothermal agent candidate. However, the stability and tumor targeting are still great obstacles for its wide application. In this work, C-phycocyanin (CPC) as a tumor-associated macrophages (TAMs) targeted vehicle was used to fabricate noncovalent ICG conjugate of CPC (ICG@CPC) via self-assembly in aqueous media. Compared to free ICG, ICG@CPC displays improved stabilities in aqueous solutions and under light irradiation and threefold increase in photothermal conversion efficiency. The in vitro results indicated that ICG@CPC could be selectively internalized into J774A.1 cells via SR-A-mediated endocytosis and lead to enhanced photocytotoxicity against J774A.1 cells. In vivo results showed that ICG@CPC had significantly improved drug accumulation in the tumor and photothermal therapeutic efficacy relative to ICG alone. This study for the first time utilizes CPC as a TAMs-targeted nanocarrier for ICG and may promote further rational design of ICG-based photothermal nanodrugs for precise and efficient cancer theranosis.

The interplay of haze characteristics on mortality in the Pearl River Delta of China.

To estimate the mortality risk from haze and the modifying effects by three characteristics of haze (intensity, duration and timing), data on haze and mortality in the Pearl River Delta region from 2013 to 2016 were collected. We first estimated mortality risk during haze days compared with non-haze days. Then we classified haze into several categories by considering one or any two of the three haze characteristics together, and further calculated the mortality risks separately. The mortality risk increased 5.0% (95% confidence intervals (CI): 3.1%-6.9%) during hazy days compared with non-haze days, with larger effect for the elderly ≥ 85 years old (Excess risk (ER): 8.7%, 95% CI: 3.9%-13.6%) than other age groups. Mortality risk increased in longer haze (ER: 4.4%, 95% CI: 2.9%-6.0%) compared with shorter haze (ER: 1.9%, 95% CI: 0.7%-3.2%). The greatest effect of any two of haze characteristics was observed when haze was intense and long (ER: 4.8%, 95% CI: 3.0%-6.6%). Our study indicates that haze significantly increased mortality risk in the Pearl River Delta. The health effects of haze may be under-estimated when using a single air pollutant concentration during haze periods to assess health risk of haze events. The haze intensity, duration, and time of occurrence should be accounted for in appropriate risk assessment of haze.

Associations of maternal ozone exposures during pregnancy with maternal blood pressure and risk of hypertensive disorders of pregnancy: A birth cohort study in Guangzhou, China.

Although studies have assessed the associations of maternal exposure to ozone (O3) during pregnancy with blood pressure and the risk of hypertensive disorders of pregnancy (HDP), the results were inconsistent. Furthermore, no studies have been conducted in China where the ambient O3 concentration continuedly increased. The present study aimed to estimate the effects of maternal exposure to O3 during pregnancy on the HDP risk, systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP). All participants of pregnant women were selected from the prospective birth cohort study on Prenatal Environments and Offspring Health conducted in Guangzhou, China. A spatiotemporal land-use-regression model was used to estimate individual monthly air pollution exposure from three months before pregnancy to childbirth date. Information on HDP, SBP, DBP and PP was obtained from maternal medical records. A Logistic regression model and a mixed linear model were used to estimate the associations of maternal exposure to O3 with the risk of HDP and blood pressure (SBP, DBP and PP), respectively. We found significant associations of maternal exposure to O3 during the third (OR = 1.31, 95%CI: 1.07, 1.60) and the second month (OR = 1.25, 95%CI: 1.02, 1.51) before pregnancy with the risk of HDP. Observed significantly positive associations of O3 exposures with SBP, DBP and PP during the two months before pregnancy and during the early pregnancy. The peak effects of O3 exposure on SBP, DBP and PP were respectively observed during the second month of pregnancy (ß = 1.07  mmHg, 95%CI: 0.84, 1.31  mmHg), the first month before pregnancy (ß = 0.40  mmHg, 95%CI: 0.21, 0.50  mmHg) and the second month of pregnancy (ß = 0.78  mmHg, 95%CI: 0.59, 0.97  mmHg). Our results suggest that maternal exposure to O3 were positively associated with blood pressure and the risk of HDP, and the period from three months before pregnancy to the first trimester might be the critical exposure window.

Automated machine learning-based model for the prediction of delirium in patients after surgery for degenerative spinal disease.

OBJECTIVE: This study used machine learning algorithms to identify critical variables and predict postoperative delirium (POD) in patients with degenerative spinal disease. METHODS: We included 663 patients who underwent surgery for degenerative spinal disease and received general anesthesia. The LASSO method was used to screen essential features associated with POD. Clinical characteristics, preoperative laboratory parameters, and intraoperative variables were reviewed and were used to construct nine machine learning models including a training set and validation set (80% of participants), and were then evaluated in the rest of the study sample (20% of participants). The area under the receiver-operating characteristic curve (AUROC) and Brier scores were used to compare the prediction performances of different models. The eXtreme Gradient Boosting algorithms (XGBOOST) model was used to predict POD. The SHapley Additive exPlanations (SHAP) package was used to interpret the XGBOOST model. Data of 49 patients were prospectively collected for model validation. RESULTS: The XGBOOST model outperformed the other classifier models in the training set (area under the curve [AUC]: 92.8%, 95% confidence interval [CI]: 90.7%-95.0%), validation set (AUC: 87.0%, 95% CI: 80.7%-93.3%). This model also achieved the lowest Brier Score. Twelve vital variables, including age, serum albumin, the admission-to-surgery time interval, C-reactive protein level, hypertension, intraoperative blood loss, intraoperative minimum blood pressure, cardiovascular-cerebrovascular disease, smoking, alcohol consumption, pulmonary disease, and admission-intraoperative maximum blood pressure difference, were selected. The XGBOOST model performed well in the prospective cohort (accuracy: 85.71%). CONCLUSION: A machine learning model and a web predictor for delirium after surgery for the degenerative spinal disease were successfully developed to demonstrate the extent of POD risk during the perioperative period, which could guide appropriate preventive measures for high-risk patients.

The time-varying transmission dynamics of COVID-19 and synchronous public health interventions in China.

OBJECTIVES: We aimed to estimate the time-varying transmission dynamics of COVID-19 in China, Wuhan City, and Guangdong province, and compare to that of severe acute respiratory syndrome (SARS). METHODS: Data on COVID-19 cases in China up to 20 March 2020 was collected from epidemiological investigations or official websites. Data on SARS cases in Guangdong Province, Beijing, and Hong Kong during 2002-3 was also obtained. We estimated the doubling time, basic reproduction number (R0), and time-varying reproduction number (Rt) of COVID-19 and SARS. RESULTS: As of 20 March 2020, 80,739 locally acquired COVID-19 cases were identified in mainland China, with most cases reported between 20 January and 29 February 2020. The R0 value of COVID-19 in China and Wuhan was 5.0 and 4.8, respectively, which was greater than the R0 value of SARS in Guangdong (R0 = 2.3), Hong Kong (R0 = 2.3), and Beijing (R0 = 2.6). At the start of the COVID-19 epidemic, the Rt value in China peaked at 8.4 and then declined quickly to below 1.0 in one month. With SARS, the Rt curve saw fluctuations with more than one peak, the highest peak was lower than that for COVID-19. CONCLUSIONS: COVID-19 has much higher transmissibility than SARS, however, a series of prevention and control interventions to suppress the outbreak were effective. Sustained efforts are needed to prevent the rebound of the epidemic in the context of the global pandemic.

Associations of ambient temperature exposure during pregnancy with the risk of miscarriage and the modification effects of greenness in Guangdong, China.

Miscarriage is one of the commonest complications of pregnancy. Although previous studies suggested that environmental factors were important causes of miscarriage, evidence is still inadequate. Here, we examined the association of maternal exposure to temperature with the risk of miscarriage and further assessed the modifying effects of surrounding residential greenness. A case-control study was conducted at a large hospital in Guangzhou, China. All participants' information was extracted from hospital records. An inverse distance weighted method was used to estimate the temperature exposure at each residential address, where the greenness was measured by Normalized Difference Vegetation Index (NDVI). A logistic regression model was applied to estimate the association of temperature exposure with the risk of miscarriage. A total of 2044 cases of miscarriage and 2285 controls were included in the present study. We observed a generally non-linear positive relationship between temperature exposure and the risk of miscarriage. More pronounced effects of high temperatures vs. low temperatures were found during the two months prior to hospitalization than in other periods. The odds ratio (OR) of 29.4 °C (95th centile) compared with 15 °C during the first month prior to hospitalization was 1.480 (95% CI: 1.021-2.145). Smaller effects of temperatures were seen on the risk of miscarriage among participants with moderately great surrounding greenness compared with those with less greenness. We concluded that maternal exposure to moderately high temperature during pregnancy may increase the risk of miscarriage, but the modifying effects of greenness on these associations need to be further tested in future studies.

A spatiotemporal land-use-regression model to assess individual level long-term exposure to ambient fine particulate matters.

We aimed to establish a spatiotemporal land-use-regression (ST-LUR) model assessing individual level long-term exposure to fine particulate matters (PM2.5) among 6627 adults enrolled in Guangdong province, China from 2015 to 2016. We collected weekly average PM2.5 concentration (from the air quality monitoring stations) and visibility, population density, road density and types of land use of each air quality monitoring station and participant's residential address from April 2013 to December 2016. A ST-LUR model was established using these spatiotemporal data, and was employed to estimate the weekly average PM2.5 concentration of each individual residential address. Data analysis was carried out by R software (version 3.5.1) and the SpatioTemporal package was used. The results showed that the ST-LUR model applying the land use data extracted using a buffer radius of 1300 m had the best modelling fitness. The results of 10-fold cross validation showed that the R2 was 88.86% and the RMSE (Root mean square error) was 5.65 µg/m3. The two-year average of PM2.5 prior to the date of investigation were calculated for each participant. This study provided a novel method to precisely assess individual level long-term exposure to ambient PM2.5, which may extend our understanding on the health impacts of air pollution. •Variables input in the spatiotemporal land-use-regression (ST-LUR) model include visibility, population density, road density, and types of land use.•The land use data should be extracted using a buffer radius of 1300 m.•The R2 of the ST-LUR model was 88.86% and the RMSE was 5.65 µg/m3, indicating the good performance of the model.

C-Phycocyanin as a tumour-associated macrophage-targeted photosensitiser and a vehicle of phthalocyanine for enhanced photodynamic therapy.

C-Phycocyanin (CPC) as a tumour-associated macrophage (TAM)-targeted photosensitiser has been first proved, and used as a vehicle of zinc phthalocyanine (ZnPc) to fabricate a ZnPc-CPC conjugate, which exhibits an efficient in vitro photodynamic activity, and selectively accumulates in tumour sites probably due to the affinity to TAM.

Mono- and tetra-substituted zinc(II) phthalocyanines containing morpholinyl moieties: Synthesis, antifungal photodynamic activities, and structure-activity relationships.

A series of zinc(II) phthalocyanines (ZnPcs) mono-substituted and tetra-substituted with morpholinyl moieties and their quaternized derivatives have been synthesized and evaluated for their antifungal photodynamic activities toward Candida albicans. The α-substituted, quaternized, and mono-substituted ZnPcs are found to have higher antifungal photoactivity than ß-substituted, neutral, and tetra-substituted counterparts. The cationic α-mono-substituted ZnPc (6a) exhibits the highest photocytotoxicity. Moreover, it is more potent than axially di-substituted analogue. The different photocytotoxicities of these compounds have also been rationalized by investigating their spectroscopic and photochemical properties, aggregation trend, partition coefficients, and cellular uptake. The IC90 value of 6a against C. albicans cells is as low as 3.3 µM with a light dose of 27 J cm(-2), meaning that 6a is a promising candidate as the antifungal photosensitizer for future investigations.