A review of aptamer-conjugated nanomaterials for analytical sample preparation: Classification according to the utilized nanomaterials

BACKGROUND

Sample extraction before detection is a critical step in analysis. Since targets of interest are often found in complex matrices, the sample can not be directly introduced to the analytical instrument. Nanomaterials with unique physical-chemical properties are excellent supports for use in sorbent-based extraction. However, they lack selectivity and thus need to be functionalized with target-capturing molecules. Antibodies and molecularly imprinted polymers (MIPs) can be used for this purpose, but they have some problems that limit their practical applications. Hence, functionalization of nanomaterials for selectivity remains a problem.

RESULTS

Nucleic acid aptamers are affinity reagents that can provide superiority to antibodies since they can be selected in vitro and at a lower cost. Moreover, aptamers can be chemically synthesized and easily modified with different functional groups. Hence, aptamers are good candidates to impart selectivity to the nanomaterials. Recent studies focus on the integration of aptamers with magnetic nanoparticles, carbon-based nanomaterials, metal-organic frameworks, gold nanoparticles, gold nanorods, silica nanomaterials, and nanofibers. The unique properties of nanomaterials and aptamers make the aptamer-conjugated nanomaterials attractive for use in sample preparation. Aptamer-functionalized nanomaterials have been successfully used for selective extraction of proteins, small molecules, and cells from different types of complex samples such as serum, urine, and milk. In particular, magnetic nanoparticles have a wider use due to the rapid extraction of the sample under magnetic field.

SIGNIFICANCE

In this review, we aim to emphasize how beneficial features of nanomaterials and aptamers could be combined for extraction or enrichment of the analytes from complex samples. We aim to highlight that the benefits are twofold in terms of selectivity and efficiency when employing nanomaterials and aptamers together as a single platform.

Positive bag lavage cytology during thoracoscopic surgery for lung cancer is a significant predictor of locoregional recurrence

OBJECTIVES

Advances in thoracoscopic surgery have made skin incisions smaller, but there are concerns about cancer cell contamination during sample extraction. We performed retrieval bag lavage cytology (BLC) during thoracoscopic surgery to evaluate the risk of cancer dissemination and the prognostic influence of BLC status.

METHODS

BLC was investigated in 893 patients who underwent thoracoscopic lobectomy or segmentectomy for lung cancer between 2013 and 2018. The clinicopathological features and prognosis were compared between the BLC-positive and BLC-negative groups.

RESULTS

Forty-nine patients (5.5%) were positive for BLC. BLC correlated with pleural invasion (49.0% vs. 12.9%, P < 0.001); however, BLC was positive in 3.3% of cases without pleural invasion. Multivariate analysis revealed that tumor size, lymph node metastasis, lymphatic and pleural invasion were predictive factors for positive BLC. Prognosis was poorer in the BLC-positive group than in the BLC-negative group (5-year overall survival, 73.6% vs. 90.2%, P < 0.001); nevertheless, positive BLC was not an independent prognostic factor. The locoregional recurrence rate was higher among BLC-positive patients than among BLC-negative patients, whereas there was no significant difference in the distant recurrence rate. Positive BLC was associated with locoregional recurrence (hazard ratio 1.87, P = 0.044) and the correlation was stronger in stage I lung cancer. There were no cases of extraction bag breakage or port-site recurrence.

CONCLUSIONS

BLC positivity was correlated with the risk of locoregional recurrence in patients with surgically resected lung cancer, although it was not an independent prognostic factor. Careful manipulation is essential for extracting specimens from the thoracic cavity.

Iron nanoparticles decorated hierarchical carbon fiber forest for the magnetic solid-phase extraction of multi-pesticide residues from water samples

This study describes a versatile, robust and fast sample pre-concentration novel method based on chemical vapour deposition grown iron nanoparticles dispersed hierarchical carbon fiber forest (Fe-ACF/CNF) for the determination of multi-pesticide residue in water samples. This method was developed by the implementation of Fe-ACF/CNF to magnetic solid-phase extraction method (MSPE) for the adsorption of twenty-nine pesticides of various classes using gas chromatography equipped with an electron capture detector. Fe-ACF/CNF was grown via tip growth mechanism and Fe-nanoparticles are moved to the tip of CNF. The presence of Fe-nanoparticles is responsible for the magnetic property of proposed adsorbents. The Fe-ACF/CNF is competent enough to extract twenty-nine pesticides of different physico-chemical characteristics from water samples. All the predominant parameters including the amount of sorbent desorption time, temperature, sonication effect, regeneration, and reusability of Fe-ACF/CNF were thoroughly investigated. Acceptable linearity was obtained in the range of 20-500 μg/L with a correlation coefficient value ≥ 0.990 for all pesticides. The accuracy of the developed method was evaluated and the obtained recovery of the spiked samples was within 70-120% (standard deviation ≤ 15%) and reusability up to the 4th cycle. The limit of detection and quantification values was in the range of 1.44-5.15 and 4.76-17.0 μg/L, respectively. The obtained results are also cross verified with real water samples from the Gomti river (Lucknow, India) and shown the excellent extraction efficiency of Fe-ACF/CNF.

Smart materials for point-of-care testing: From sample extraction to analyte sensing and readout signal generator

The last decade has seen a surge of technical developments in the field on point-of-care testing (POCT). While these developments are extremely diverse, the common aim is to implement improved methods for quick, reliable and inexpensive diagnosis of patients within the clinical setting. While examples of successful introduction and use of POCT techniques are growing, further developments are still necessary to create POCT devices with better portability, usability and performance. Advances in smart materials emerge as potentially valuable know-hows to provide a competitive edge to the development of next generation POCT devices. This review describes the key advantages of adopting smart material-based technologies at different analytical stages of a POCT platform. Under these analytical stages which involves sample pre-treatment, analyte sensing and readout signal generator, several concepts and approaches from contemporary research work in using smart material-based technologies will be the major focus in this review. Lastly, challenges and potential outlook in implementing materials technologies from the application point of view for POCT will be discussed.

Comparison of modified Matyash method to conventional solvent systems for polar metabolite and lipid extractions

In the last decade, metabolomics has experienced significant advances in the throughput and robustness of analytical methodologies. Yet the preparation of biofluids and low-mass tissue samples remains a laborious and potentially inconsistent manual process, and a significant bottleneck for high-throughput metabolomics. To address this, we have compared three different sample extraction solvent systems in three diverse sample types with the purpose of selecting an optimum protocol for subsequent automation of sample preparation. We have investigated and re-optimised the solvent ratios in the recently introduced methyl tert-butyl ether (MTBE)/methanol/water solvent system (here termed modified Matyash; 2.6/2.0/2.4, v/v/v) and compared it to the original Matyash method (10/3/2.5, v/v/v) and the conventional chloroform/methanol/water (stepwise Bligh and Dyer, 2.0/2.0/1.8, v/v/v) using two biofluids (human serum and urine) and one tissue (whole Daphnia magna). This is the first report of the use of the Matyash method for extracting metabolites from the US National Institutes of Health (NIH) model organism D. magna. Extracted samples were analysed by non-targeted direct infusion mass spectrometry metabolomics or LC-MS metabolomics. Overall, the modified Matyash method yielded a higher number of peaks and putatively annotated metabolites compared to the original Matyash method (1-29% more peaks and 1-30% more metabolites) and the Bligh and Dyer method (4-20% more peaks and 1-41% more metabolites). Additionally the modified Matyash method was superior when considering metabolite intensities. The reproducibility of the modified Matyash method was higher than other methods (in 10 out of 12 datasets, compared to the original Matyash method; and in 8 out of 12 datasets, compared to the Bligh and Dyer method), based upon the observation of a lower mRSD of peak intensities. In conclusion, the modified Matyash method tended to provide a higher yield and reproducibility for most sample types in this study compared to two widely used methods.

Analysis of the endogenous human serum peptides by on-line extraction with restricted-access material and HPLC-MS/MS identification

The selective extraction of endogenous serum peptides has been a challenge due to the high abundant proteins present in serum. Here a simple on-line extraction of peptides from human serum using strong cation-exchange diol silica restricted-access materials (SCX-RAM) coupled with two-dimensional RP-RP liquid chromatography mass spectrometry was developed. The operation of the on-line extraction system is simple to use and does not need complex equipments. The two-dimensional RP-RP was proved to be orthogonal and efficient to separate peptides extracted from human serum.