Metabolic Recoding of NSUN2-Mediated m5C Modification Promotes the Progression of Colorectal Cancer via the NSUN2/YBX1/m5C-ENO1 Positive Feedback Loop.

The RNA modification, 5-methylcytosine (m5C), has recently gained prominence as a pivotal post-transcriptional regulator of gene expression, intricately intertwined with various tumorigenic processes. However, the exact mechanisms governing m5C modifications during the onset and progression of colorectal cancer (CRC) remain unclear. Here, it is determined that the m5C methyltransferase NSUN2 exhibits significantly elevated expression and exerts an oncogenic function in CRC. Mechanistically, NSUN2 and YBX1 are identified as the "writer" and "reader" of ENO1, culminating in the reprogramming of the glucose metabolism and increased production of lactic acid in an m5C-dependent manner. The accumulation of lactic acid derived from CRC cells, in turn, activates the transcription of NSUN2 through histone H3K18 lactylation (H3K18la), and induces the lactylation of NSUN2 at the Lys356 residue (K356), which is crucial for capturing target RNAs. Together, these findings reveal an intriguing positive feedback loop involving the NSUN2/YBX1/m5C-ENO1 signaling axis, thereby bridging the connection between metabolic reprogramming and epigenetic remodeling, which may shed light on the therapeutic potential of combining an NSUN2 inhibitor with immunotherapy for CRC.

Clear cell renal cell carcinoma with syncytial giant cells: Not that rare.

Syncytial giant cells (SGCs) are neoplastic giant cells of epithelial origin. The nuclear morphology of SGCs is uniform and similar to those of adjacent mononuclear tumor cells. Clear cell renal cell carcinoma (ccRCC) with SGCs is a rare microscopic morphology. In this study, the clinical and pathological data of 16 ccRCC cases with SGCs were retrospectively reviewed. The incidence of SGCs in pathological stages pT3 and above (12.1%, 8/66) was significantly higher than that in pT1 and pT2 (2.6%, 8/306) (P = 0.002). The incidence of SGCs in the WHO/ISUP nuclear grade 3 or 4 ccRCC (12.4%, 14/113) was significantly higher than that in grade 1 or 2 (0.8%, 2/259) (P < 0.001). Two forms of SGCs were observed, some exhibited nuclear pyknosis and degeneration. Of the 16 cases, eight cases were accompanied by necrosis and seven cases had lymphovascular invasion. Both SGCs and mononuclear tumor cells were positive for ccRCC markers (PAX8, CAIX, CD10 and Vimentin). None of the SGC nuclei were positive for Ki-67. Follow-up information was available on 14 patients, with a median follow-up time of 27.5 months. Ten patients were alive without disease, three were alive with metastatic disease, and one patient died 10 months after surgery. These findings indicated that SGCs are not rare, especially in ccRCC with high nuclear grade and pathological stage, and often co-exist with other adverse prognostic features. SGCs may be senescent tumor cells, the presence of SGCs should not be considered as Fuhrman and WHO/ISUP nuclear grading 4.

An Automated Breast Volume Scanner-Based Intra- and Peritumoral Radiomics Nomogram for the Preoperative Prediction of Expression of Ki-67 in Breast Malignancy.

RATIONALE AND OBJECTIVES: This study aimed to create and verify a nomogram for preoperative prediction of Ki-67 expression in breast malignancy to assist in the development of personalized treatment strategies. MATERIALS AND METHODS: This retrospective study received approval from the institutional review board and included a cohort of 197 patients with breast malignancy who were admitted to our hospital. Ki-67 expression was divided into two groups based on a 14% threshold: low and high. A radiomics signature was built utilizing 1702 radiomics features based on an intra- and peritumoral (10 mm) regions of interest. Using multivariate logistic regression, radiomics signature, and ultrasound (US) characteristics, the nomogram was developed. To evaluate the model's calibration, clinical application, and predictive ability, decision curve analysis (DCA), the calibration curve, and the receiver operating characteristic curve were used, respectively. RESULTS: The final nomogram included three independent predictors: tumor size (P = .037), radiomics signature (P < .001), and US-reported lymph node status (P = .018). The nomogram exhibited satisfactory performance in the training cohort, demonstrating a specificity of 0.944, a sensitivity of 0.745, and an area under the curve (AUC) of 0.905. The validation cohort recorded a specificity of 0.909, a sensitivity of 0.727, and an AUC of 0.882. The DCA showed the nomogram's clinical utility, and the calibration curve revealed a high consistency among the expected and detected values. CONCLUSION: The nomogram used in this investigation can accurately predict Ki-67 expression in people with malignant breast tumors, helping to develop personalized treatment approaches.

Nomogram Based on Body Composition and Prognostic Nutritional Index Predicts Survival After Curative Resection of Gastric Cancer.

RATIONALE AND OBJECTIVES: This study aimed to identify independent prognostic factors for gastric cancer (GC) patients after curative resection using quantitative computed tomography (QCT) combined with prognostic nutritional index (PNI), and to develop a nomogram prediction model for individualized prognosis. MATERIALS AND METHODS: This study retrospectively analyzed 119 patients with GC who underwent curative resection from January 2016 to March 2018. The patients' preoperative clinical pathological data were recorded, and all patients underwent QCT scans before and after curative resection to obtain QCT parameters: bone mineral density (BMD), skeletal muscle area (SMA), visceral fat area (VFA), subcutaneous fat area (SFA) and CT fat fraction (CTFF), then relative rate of change in each parameter (ΔBMD, ΔSMA, ΔVFA, ΔSFA, ΔCTFF) was calculated after time normalization. Multivariate Cox proportional hazards was used to establish a nomogram model that based on independent prognostic factors. The concordance index (C-index), area under the time-dependent receiver operating characteristic (ROC) curve and clinical decision curve were used to evaluate the predictive performance and clinical benefit of the nomogram model． RESULTS: This study found that ΔCTFF, ΔVFA, ΔBMD and PNI are independent prognostic factors for overall survival (OS) (hazard ratio: 1.034, 0.895, 0.976, 2.951, respectively, all p < 0.05). The established nomogram model could predict the area under the ROC curve of OS at 1, 3 and 5 years as 0.816, 0.815 and 0.881, respectively. The C-index was 0.743 (95% CI, 0.684-0.801), and the decision curve analysis showed that this model has good clinical net benefit. CONCLUSION: The nomogram model based on body composition and PNI is reliable in predicting the individualized survival of underwent curative resection for GC patients.

Machine learning-based predictive model for the differential diagnosis of ≤ 5 cm gastric stromal tumor and gastric schwannoma based on CT images.

The clinical symptoms of ≤ 5 cm gastric stromal tumor (GST) and gastric schwannoma (GS) are similar, but the treatment regimens are different. This study explored the value of computed tomography (CT) combined with machine learning (ML) algorithms to find the best model to discriminate them. A total of 126 patients with GST ≤ 5 cm and 35 patients with GS ≤ 5 during 2013-2022 were included. CT imaging features included qualitative data (tumor location, growth pattern, lobulation, surface ulcer status, necrosis, calcification, and surrounding lymph nodes) and quantitative data [long diameter (LD); short diameter (SD); LD/SD ratio; degree of enhancement (DE); heterogeneous degree (HD)]. Patients were randomly divided into a training set (n = 112) and test set (n = 49) using 7:3 stratified sampling. The univariate and multivariate logistic regression analysis were used to identify independent risk factors. Five ML algorithms were used to build prediction models: Support Vector Machine, k-Nearest Neighbor, Random Forest, Extra Trees, and Extreme Gradient Boosting Machine. The analysis identified that HDv, lobulation, and tumor growth site were independent risk factors (P < 0.05). We should focus on these three imaging features of tumors, which are relatively easy to obtain. The area under the curve for the SVM, KNN, RF, ET, and XGBoost prediction models were, respectively, 0.790, 0.895, 0.978, 0.988, and 0.946 for the training set, and were, respectively, 0.848, 0.892, 0.887, 0.912, and 0.867 for the test set. The CT combined with ML algorithms generated predictive models to improve the differential diagnosis of ≤ 5 cm GST and GS which has important clinical practical value. The Extra Trees algorithm resulted in the optimal model.

Deep learning radiomics for prediction of axillary lymph node metastasis in patients with clinical stage T1-2 breast cancer.

Background: This study investigates whether deep learning radiomics of conventional ultrasound images can predict preoperative axillary lymph node (ALN) status in patients with clinical stages T1-2 breast cancer (BC). Methods: This study retrospectively analyzed the preoperative ultrasound data of 892 patients with BC, who were classified into training (n=535), validation (n=178), and test (n=179) cohorts. Linear combinations of the selected features were weighted by their coefficients to obtain the predicted score. Then, deep learning radiomic features were extracted from the ultrasound images to evaluate the ALN status. Receiver-operating characteristic curves were drawn, followed by the calculation of the area under the curve (AUC) to assess the accuracy of the prediction model in predicting axillary lymph node metastasis (ALNM) in the three cohorts. Results: Deep learning radiomics combined with radiomics and clinical parameters was the optimal diagnostic predictor of the ALN status in the absence and presence of ALNM, with the AUC of 0.920 (95% confidence interval: 0.872 and 0.968, respectively). Additionally, this combination could also differentiate low-load ALNM [N + (1-2)] from heavy-load ALNM with ≥3 positive nodes [N + (≥3)] in the test cohort, with the AUC of 0.819 (95% confidence interval: 0.568 and 1.00, respectively). Conclusions: Conclusively, deep learning radiomics of ultrasound images is a non-invasive approach to predicting preoperative ALNM in BC.

Efficient photoelectrochemical aptasensing of di-2-ethylhexyl phthalate in environmental samples based on N, S co-doped graphene quantum dots/TiO2 nanorods.

An efficient photoelectrochemical (PEC) sensing platform was developed for detection of di-2-ethylhexyl phthalate (DEHP) based on nitrogen and sulfur co-doped graphene quantum dots/TiO2 nanorods (N, S-GQDs/TiO2 NRs) coupling with exonuclease I (Exo I)-assisted target recycling for remarkable signal amplification. N, S-GQDs uniformly grown on TiO2 NRs by simple hydrothermal method showed high electron-hole separation efficiency and superior photoelectric performance, which was explored as the photoactive substrate for anchoring anti-DEHP aptamer and its complementary DNA (cDNA). With the addition of DEHP, aptamer molecules fell from the electrode surface owing to the specific recognition of aptamer to DEHP, resulting in the increment of photocurrent signal. At this moment, Exo I could stimulate aptamer hydrolysis in the aptamer-DEHP complexes, so that DEHP was released from the complexes to take part in the next reaction cycling, which remarkably increasing the photocurrent response and achieving signal amplification. The designed PEC sensing platform exhibited excellent analytical performance for DEHP with a low detection limit of 0.1 pg L-1. Also, its applications in real samples were further investigated in detail. Thus, the established method would provide a simple and efficient tool for DEHP or other pollutants monitoring in the environment.

CuO nanorod-decorated hemin-graphene with enhanced peroxidase-mimicking performance for the colorimetric and electrochemical determination of 4-aminophenol with a smartphone.

The detection of 4-aminophenol (4-AP) is of critical importance due to its high toxicity, and the development of accurate, sensitive, and portable methods for this purpose is essential. Here, a facile colorimetric and electrochemical dual-mode sensor based on a CuO nanorod-decorated hemin-functionalized graphene nanocomposite (CuO/H-Gr) is successfully constructed for the detection of 4-AP. CuO/H-Gr exhibited superior peroxidase-mimicking activity, catalyzing the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 and generating a colorimetric signal. The catalytic system was found to contain hydroxyl radicals, as revealed by reactive oxygen species trials. Meanwhile, TMB was found to be an electroactive indicator that could be oxidized on a glassy carbon electrode. In the presence of CuO/H-Gr and H2O2, an enhanced electrochemical signal of TMB was generated. Upon the addition of 4-AP, the catalytic performance of CuO/H-Gr in the oxidation of TMB was significantly reduced, leading to a decrease in colorimetric and electrochemical signals. Based on this, a dual-mode sensor for the detection of 4-AP was developed. The linear response ranges for colorimetric and electrochemical sensors are 1.00-200 µM and 0.0100-300 µM, with detection limits of 0.687 µM and 0.00756 µM, respectively. Real water samples were tested to estimate the feasibility of the dual-mode sensor, and the recoveries were found to be consistent with those obtained by high-performance liquid chromatography. In addition, a smartphone-based assay was used to evaluate the levels of 4-AP, which opened a new path for on-site detection.

Nickel hexacyanoferrate nanoparticle-decorated 3D rGO composites-based electrochemical sensing platform for detection of di-2-ethylhexyl phthalate.

A label-free and efficient electrochemical (EC) sensing platform for di-2-ethylhexyl phthalate (DEHP) was developed based on in situ probe nickel hexacyanoferrate nanoparticle (NiHCF NP)-decorated three-dimensional reduced graphene oxide (3D rGO) composites. NiHCF NPs in the composites as an in situ probe show a pair of well-defined peaks with good reversibility and stability. Coupling 3D rGO with NiHCF NPs not only improved the electron transfer capability of NiHCF NPs but also provided more sites for aptamer immobilization. The synthesized NiHCF NP-decorated 3D rGO composites were used to act as a substrate for the immobilization of anti-DEHP aptamer by the covalent bonding method. The designed EC sensing platform displays excellent sensing performance for DEHP with a low detection limit of 3.64 pg/L, and a linear working range of 0.01 - 1000 ng/L. The application of the sensing platform to actual environmental samples was studied and satisfactory results were obtained. Thus, the proposed EC sensing platform would provide a potential tool for efficient detection of pollutants in the environment.

Triple Amplification Ratiometric Electrochemical Aptasensor for CA125 Based on H-Gr/SH-ß-CD@PdPtNFs.

A triple-amplified and ratiometric electrochemical aptasensor for CA125 was designed based on hemin-graphene/SH-ß-cyclodextrin@PdPt nanoflower (H-Gr/SH-ß-CD@PdPtNF) composites and an exonuclease I (Exo I)-assisted strategy. In the nanocomposite, hemin acts as an internal reference signal owing to the reversible heminox/heminred pair. PdPtNFs can significantly improve the electron transfer rate. SH-ß-CD can efficiently enrich quercetin probes through host-guest recognition and increase the second indicator signal. In the presence of CA125, due to the specific binding between the aptamer and CA125, the conformational change of dsDNA (designed by the CA125 aptamer and its complementary DNA) results in the release of quercetin embedded in dsDNA. Subsequently, the free quercetin and DNA fragments are enriched on the H-Gr/SH-ß-CD@PdPtNF-modified electrode. Thus, an enhanced oxidation peak from quercetin (IQ) and a reduced peak from hemin (Ihemin) can indicate the same biological identification event. In addition, the recycling amplification of CA125 by Exo I can effectively assist the increase of the quercetin signal. The value of IQ/Ihemin is linear with the concentration of CA125 in the range from 6.0 × 10-4 to 1.0 × 103 ng/mL, and the limit of detection is 1.4 × 10-4 ng/mL. The recovery of CA125 in human blood serum samples was from 99.2 to 104.4%. The proposed sensor is sensitive and reliable, which provides an avenue for the development of triple amplification and ratiometric signal strategies for detecting tumor markers in clinical diagnostics.

Design an efficient photoelectrochemical aptasensor for PCB72 based on CdTe@CdS core@shell quantum dots-decorated TiO2 nanotubes.

In this work, an efficient and novel photoelectrochemical (PEC) aptasensor for 2,3',5,5'-tetrachlorobiphenyl (PCB72) was constructed based on CdTe@CdS core@shell quantum dots (CdTe@CdS QDs)-decorated TiO2 nanotubes (TiO2 NTs). CdTe@CdS QDs were prepared by the combination of CdTe and CdS with a proper lattice mismatch. Due to their large band offsets, core@shell QDs can reduce undesirable carrier recombination, significantly improving their charge separation efficiency. Then the synthesized CdTe@CdS QDs were modified on TiO2 NTs (CdTe@CdS QDs/TiO2 NTs) through electrostatic adsorption method. The as-prepared composites exhibit a wide visible light absorption range, good PEC activity and high photoelectric conversion efficiency. Also, the PEC aptasensor prepared via the immobilization of anti-PCB72 aptamer on the composites exhibits outstanding analytical performance with high sensitivity and specificity for PCB72 under visible-light irradiation, achieving a detection limit as low as 0.03 ng/L. It was also applied to detect PCB72 in four different real environmental samples with satisfactory results.

m5C regulator-mediated modification patterns and tumor microenvironment infiltration characterization in colorectal cancer: One step closer to precision medicine.

Background: The RNA modification 5-methylcytosine (m5C) is one of the most prevalent post-transcriptional modifications, with increasing evidence demonstrating its extensive involvement in the tumorigenesis and progression of various cancers. Colorectal cancer (CRC) is the third most common cancer and second leading cause of cancer-related deaths worldwide. However, the role of m5C modulators in shaping tumor microenvironment (TME) heterogeneity and regulating immune cell infiltration in CRC requires further clarification. Results: The transcriptomic sequencing data of 18 m5C regulators and clinical data of patients with CRC were obtained from The Cancer Genome Atlas (TCGA) and systematically evaluated. We found that 16 m5C regulators were differentially expressed between CRC and normal tissues. Unsupervised cluster analysis was then performed and revealed two distinct m5C modification patterns that yielded different clinical prognoses and biological functions in CRC. We demonstrated that the m5C score constructed from eight m5C-related genes showed excellent prognostic performance, with a subsequent independent analysis confirming its predictive ability in the CRC cohort. Then we developed a nomogram containing five clinical risk factors and the m5C risk score and found that the m5C score exhibited high prognostic prediction accuracy and favorable clinical applicability. Moreover, the CRC patients with low m5C score were characterized by "hot" TME exhibiting increased immune cell infiltration and higher immune checkpoint expression. These characteristics were highlighted as potential identifiers of suitable candidates for anticancer immunotherapy. Although the high m5C score represented the non-inflammatory phenotype, the CRC patients in this group exhibited high level of sensitivity to molecular-targeted therapy. Conclusion: Our comprehensive analysis indicated that the novel m5C clusters and scoring system accurately reflected the distinct prognostic signature, clinicopathological characteristics, immunological phenotypes, and stratifying therapeutic opportunities of CRC. Our findings, therefore, offer valuable insights into factors that may be targeted in the development of precision medicine-based therapeutic strategies for CRC.

Liposomes and liposome-like nanoparticles: From anti-fungal infection to the COVID-19 pandemic treatment.

The liposome is the first nanomedicine transformed into the market and applied to human patients. Since then, such phospholipid bilayer vesicles have undergone technological advancements in delivering small molecular-weight compounds and biological drugs. Numerous investigations about liposome uses were conducted in different treatment fields, including anti-tumor, anti-fungal, anti-bacterial, and clinical analgesia, owing to liposome's ability to reduce drug cytotoxicity and improve the therapeutic efficacy and combinatorial delivery. In particular, two liposomal vaccines were approved in 2021 to combat COVID-19. Herein, the clinically used liposomes are reviewed by introducing various liposomal preparations in detail that are currently proceeding in the clinic or on the market. Finally, we discuss the challenges of developing liposomes and cutting-edge liposomal delivery for biological drugs and combination therapy.

Media multitasking, depression, and anxiety of college students: Serial mediating effects of attention control and negative information attentional bias.

Background: The COVID-19 epidemic provides an environment for frequent media multitasking, which might associate with an increase in depression and anxiety. Since many studies have found that media multitasking negatively affects cognitive capacity, we propose a cognitive perspective to explore how media multitasking may associate with mental health. This study examined the potential mediating role of attention control and negative information attentional bias in the relationship between media multitasking and anxiety and depression. Methods: Participants (n = 567) were recruited from college students in China. They completed an online survey that included the Media Multitasking Inventory (MMI), Attention Control Scale (ACS), Attention to Positive and Negative Information Scale (APNI), Generalized Anxiety Disorder Scale (GAD-7), and Patient Health Questionnaire (PHQ-9). After exploring the correlations between the measures, serial mediation models were examined. Results: The results indicated significant positive correlations between media multitasking and anxiety and depression. Media multitasking, anxiety, and depression were negatively correlated with attention focusing, while positively correlated with negative information attention bias. Media multitasking did not correlate with attention shifting. Mediation modeling demonstrated that attention focusing and negative information attention bias played a serial mediating role in the relationship between media multitasking and anxiety and depression. However, the results did not support the serial mediation model through attention shifting and negative information attention bias. Conclusion: Media multitasking does not directly influence anxiety and depression, while attention focusing and negative information attention bias play serial mediating roles in their relationship. This study highlights the potential cognitive mechanisms between media multitasking and anxiety and depression, providing theoretical support for interventions in individual mental health during the epidemic.

N6-methyladenosine modification of circ_0003215 suppresses the pentose phosphate pathway and malignancy of colorectal cancer through the miR-663b/DLG4/G6PD axis.

Circular RNAs (circRNAs) are a recently discovered kind of regulatory RNAs that have emerged as critical biomarkers of various types of cancers. Metabolic reprogramming has gradually been identified as a distinct hallmark of cancer cells. The pentose phosphate pathway (PPP) plays an indispensable role in satisfying the bioenergetic and biosynthetic demands of cancer cells. However, little is known about the role of circRNAs and PPP in colorectal cancer (CRC). The novel circ_0003215 was identified at low levels in CRC and was negatively correlated with larger tumor size, higher TNM stage, and lymph node metastasis. The decreased level of circ_0003215 was resulted from the RNA degradation by m6A writer protein YTHDF2. A series of functional assays demonstrated that circ_0003215 inhibited cell proliferation, migration, invasion, and CRC tumor metastasis in vivo and in vitro. Moreover, circ_0003215 regulated the expression of DLG4 via sponging miR-663b, thereby inducing the metabolic reprogramming in CRC. Mechanismly, DLG4 inhibited the PPP through the K48-linked ubiquitination of glucose-6-phosphate dehydrogenase (G6PD). Taken together, we have identified m6A-modified circ_0003215 as a novel regulator of metabolic glucose reprogramming that inhibited the PPP and the malignant phenotype of CRC via the miR-663b/DLG4/G6PD axis.

Big Data Technology Oriented to Wetland Resource Ecosystem Value Evaluation.

In order to study a big data technology research for the evaluation of wetland resource ecosystem value. This paper proposes a wetland dimension oriented to the evaluation of wetland ecosystem services space attribute through big data coupling analysis framework. The framework used China's coastal wetlands as a case for empirical research and summarized the future direction of the research on the value evaluation of wetland ecosystem services in the era of big data. The result shows: Wetland Ecosystem Observation Network can obtain long-term series of dynamic data, remote sensing Earth observation can realize the integrated observation of space, space, and Earth, the combination of the two will help to build a wetland ecological big data observation system. The service value of China's coastal wetland ecosystem is 5010.32 × 108 yuan. The research results can effectively solve the problem of geographical heterogeneity and have reference value for the protection and management of the wetland ecosystem.

Enhanced Effect of Qing-Ying Decoction Concurrent with Secukinumab in the Treatment of Plaque Psoriasis.

Both Qing-Ying decoction (QYD), a Traditional Chinese Medicine (TCM), and secukinumab, a fully humanized anti-interleukin-17A monoclonal antibody, have been used to treat patients with plaque psoriasis. The combined application of TCM and biologics in the treatment of psoriasis, however, has not been investigated. We enrolled a total of 68 patients with plaque psoriasis in our prospective study, and randomly assigned them to either the study group (treated with secukinumab plus QYD), or the control group (treated with secukinumab alone). After 12- and 16-week treatment, the Psoriasis Area and Severity Index (PASI) score and the TCM score were significantly reduced in both the study and the control groups. However, the reduction in PASI and TCM scores was more significant in the study group than in the control group (12-week: PASI: 5.29 ± 0.27 vs 8.87 ± 0.38, respectively; P < .01; TCM: 5.83 ± 0.21 vs 12.39 ± 1.23, respectively; P < .01; 16-week: PASI score: 4.76 ± 0.18 vs 8.36 ± 0.31, respectively; TCM score: 4.98 ± 0.19 vs 11.27 ± 1.13, respectively; P < .01). The total treatment efficacy rate was significantly higher in the study group (97.1%) than the control group (76.5%; P = .012). The number of CD3+ and CD4+ T cells was increased, while the number of CD8+ T cells was decreased after treatment in both groups, with more significant changes in the study group (P < .01). QYD may enhance the therapeutic outcome of secukinumab in the treatment of plaque psoriasis by further suppressing chronic skin inflammation, as well as reducing adverse events and patients' psychological stress.

A selective electrochemical chiral interface based on a carboxymethyl-ß-cyclodextrin/Pd@Au nanoparticles/3D reduced graphene oxide nanocomposite for tyrosine enantiomer recognition.

Palladium@gold nanoparticle modified three-dimensional-reduced graphene oxide (3D-rGO/Pd@Au) was coupled with carboxymethyl-ß-cyclodextrin to form a novel nanocomposite (3D-rGO/Pd@Au/CM-ß-CD). The 3D-rGO/Pd@Au/CM-ß-CD served as a chiral sensing interface for the electrochemical enantiorecognition of tyrosine (Tyr) via a differential pulse voltammetry (DPV) approach. The 3D-rGO/Pd@Au demonstrates good electrical conductivity and efficient catalytic activity as an electrochemical indicator. Simultaneously, the CM-ß-CD displays a supramolecular chiral selectivity to reveal a higher binding affinity to the target L-tyrosine (L-Tyr) than to D-tyrosine (D-Tyr). Under the optimized determining conditions, the oxidation peak current ratio of L-Tyr to D-Tyr (IL/ID) was 2.12, meanwhile, the peak currents of the two isomers were linearly proportional to the concentration over the range of 0.8-130 µM with LODs of 52 nM and 96 nM for L- and D-Tyr (S/N = 3), respectively. This approach exhibits distinguished sensitivity, excellent selectivity and good reproducibility, as well as great stability, which can accurately determine the relative content of L- or D-Tyr enantiomers in a racemic solution.

Highly sensitive and selective photoelectrochemical aptasensing of di-2-ethylhexyl phthalate based on graphene quantum dots decorated TiO2 nanotube arrays.

A photoelectrochemical (PEC) sensing platform for di-2-ethylhexyl phthalate (DEHP) was constructed using graphene quantum dots decorated TiO2 nanotube arrays (GQDs-decorated TiO2 NTs) as the transducer species and the anti-DEHP aptamer as the biological recognition element. GQDs were synthesized using the alkali-mediated hydrothermal method, and then anchored onto the TiO2 NTs uniformly and intimately via pronounced electrostatic interaction. Coupling GQDs with TiO2 NTs not only enhanced visible-light absorption, but promoted charge separation and transportation, exhibiting excellent photocurrent response, and PEC activity. Various means were conducted to explore morphologies, optical, structural and PEC properties of the materials. As an identification unit, the anti-DEHP aptamer molecules were immobilized on GQDs-decorated TiO2 NTs using a cross-linking coupling method. The developed PEC sensing platform exhibits excellent sensing behavior for DEHP, and provides a low detection limit of 0.1 ng/L, high selectivity and stability. Meanwhile, its application in real environmental samples was evaluated and satisfying results were achieved. Thus, the established sensing platform provides a promising tool to detect DEHP in the environment.