A novel photoelectrochemical aptasensor based on 3D flower-like g-C3N4/BiOI p-n heterojunction for the sensitive detection of kanamycin.

BACKGROUND: Kanamycin (KAN) residues in animal-derived foods continuously enter the human body, which will pose serious threats to human health such as hearing loss, nephrotoxicity and other complications. Therefore, to sensitively detect KAN residues by a reliable technology is extremely urgent in food quality and safety. Compared with traditional methods being limited by cost and complexity, photoelectrochemical (PEC) biosensors benefit from some merits such as rapid response, excellent sensitivity and good stability. In this study, the construction of a highly efficient PEC platform to realize KAN residues detection is discussed. RESULTS: Herein, a novel p-n heterojunction consisting of flower-like BiOI microspheres and graphite carbon nitride (g-C3N4) nanoflakes was developed to establish a PEC aptasensor for KAN detection at 0 V. The prepared g-C3N4/BiOI heterostructure showed not only significantly enhanced PEC activity due to the larger specific surface area but also greatly increased charge separation efficiency owing to the strong internal electric field. Meanwhile, using g-C3N4/BiOI as a highly efficient photoactive material for binding amine-functionalized aptamers to capture KAN, the photocurrent signals showed a 'turn off' mode to achieve the sensitive detection of KAN. The proposed PEC aptasensor exhibited linear response for KAN from 5 × 10-9 to 3 × 10-7 mol L-1 with a low detection limit of 1.31 × 10-9 mol L-1, and satisfactory recoveries (97.44-107.38 %) were obtained in real food samples analysis. SIGNIFICANCE: This work presented a novel p-n heterojunction-based PEC aptasensor with strong selectivity and stability, rendering it allowed to detect KAN in animal-derived foods including milk, honey and pork. Additionally, the detection range satisfied the MRLs for KAN specified by the national standards, demonstrating the potential application for food analysis. The study provides a new insight into the development of efficient and practical biosensors for antibiotic residues detection.

Plasma hemoglobin and the risk of death in HIV/AIDS patients treated with antiretroviral therapy.

BACKGROUND: Previous studies concerning the effect of plasma hemoglobin (HB) and other factors that may modify the risk of death in people living with HIV/AIDS (PLHIV) treated with antiretroviral therapy (ART) are limited. RESULTS: Higher HB was independently linked to a lower death risk in PLHIV, with a decrease of 29% (13%, 43%) per standard deviation (SD) increment after adjusting for CD4, VL and other potential factors [hazard ratio (HR): 0.71, 95% confidence interval (CI): 0.57-0.87, P<0.001]. In addition, the addition of HB to the predictive model containing VL and CD4 significantly improved the C-index, by 0.69% (95% CI: 0.68%-0.71%), and net discrimination, by 0.5% (95% CI: 0.0%-1.6%, P=0.040), when predicting the death risk of PLHIV. CONCLUSIONS: A lower level of HB was an independent risk factor for HIV/AIDS-associated death in PLHIV. HB combined with VL and CD4 may be an appropriate predictive model of the death risk of PLHIV. MATERIALS AND METHODS: A propensity-score matching (PSM) approach was applied to select a total of 750 PLHIV (150 deceased and 600 living) from the AIDS prevention and control information system in the Wenzhou area from 2006 to 2018. Multivariable Cox proportional hazards regression models were formulated to estimate the effect of HB. The predictive performance improvement contributed by HB was evaluated using the C-index and net reclassification improvement.

Development and validation of a prognostic nomogram for HIV/AIDS patients who underwent antiretroviral therapy: Data from a China population-based cohort.

BACKGROUND: Accurate forecast of the death risk is crucial to the administration of people living with HIV/AIDS (PLHIV). We aimed to establish and validate an effective prognosis nomogram in PLHIV receiving antiretroviral therapy (ART). METHODS: All the data were obtained from 2006 to 2018 in the Wenzhou area from China AIDS prevention and control information system. Factors included in the nomogram were determined by univariate and multiple Cox proportional hazard analysis based on the training set. The receiver operating characteristic (ROC) and calibration curves were used to assess its predictive accuracy and discriminative ability. Its clinical utility was also evaluated using decision curve analysis (DCA), X-tile analysis and Kaplan-Meier curve, respectively in an independent validation set. FINDINGS: Independent prognostic factors including haemoglobin, viral load and CD4+ T-cell count were determined and contained in the nomogram. Good agreement between the prediction by nomogram and actual observation could be detected in the calibration curve for mortality, especially in the first year. In the training cohort, AUC (95% CI) and C-index (95% CI) were 0.93 (0.90, 0.96) and 0.90 (0.85, 0.96), respectively. In the validation set, the nomogram still revealed excellent discriminations [AUC (95% CI): 0.95 (0.91, 1.00)] and good calibration [C-index (95% CI): 0.92 (0.82-1.00)]. Moreover, DCA also demonstrated that the nomogram was clinical beneficial. Additionally, participants could be classified into three distinct (low, middle and high) risk groups by the nomogram. INTERPRETATION: The nomogram presents accurate and favourable prognostic prediction for PLHIV who underwent ART. FUNDING: This work was supported by Zhejiang Basic Public Welfare Research Project (LGF19H260011), Wenzhou Basic Public Welfare Research Project (Y20180201), the Initial Scientific Research Fund (KYQD170301), the Major Project of the Eye Hospital Wenzhou the Major Project of the Eye Hospital Wenzhou Medical University (YNZD201602). Part of this work was also funded by National Natural Science Foundation of China (81670777) and Science and Technology Innovation Activity Plan and New Talents Plan for College Students in Zhejiang Province (2019R413073). The funders had no roles in study design, data collection, data analysis, interpretation and writing of the report.