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Benefiting from easy visualization and simultaneous detection of multiple targets, fluorescence microbeads are commonly used as fluorescence-sensing elements to detect pollutants in the environment. However, the application of fluorescence microbead-based sensor arrays is still limited because fluorescence dyes always suffer from self-quenching, photobleaching, and spectral overlap. Herein, three kinds of gold nanoclusters (Au NCs) were assembled with polystyrene microspheres (PS NPs) by electrostatic interaction to prepare fluorescence microbeads (PS-Au NCs), developing a sensor array for the simultaneous analysis of multiple metal ions. In this work, different PS-Au NCs showed an enhancing or quenching fluorescence response to various metal ions, owing to distinct binding capacities. Combined with the recognition algorithm from linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA), this sensor assay could realize single-component and multicomponent qualitative detection for 8 kinds of heavy metal ions (HMIs) including Cu2+, Co2+, Pb2+, Hg2+, and Ce3+. Particularly, the large surface area of PS NPs could provide a direct reaction microenvironment to improve the efficiency of the detection process. Meanwhile, the fluorescence property of Au NCs could also be enhanced by a partially effective aggregation-induced emission (AIE) effect to give better fluorescence signal output. Under optimal conditions, 8 kinds of heavy metals and their multicomponent mixtures could be identified at concentrations as low as 0.62 µM. Meanwhile, the analytical performance of this sensor assay in water samples was also verified, meeting the requirement of actual analysis. This study provides a great potential and practical example of single-batch, multicomponent identification for HMIs.

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Cell cycle regulation is largely abnormal in cancers. Molecular understanding and therapeutic targeting of the aberrant cell cycle are essential. Here, we identified that an underappreciated serine/threonine kinase, cyclin-dependent kinase-like 3 (CDKL3), crucially drives rapid cell cycle progression and cell growth in cancers. With regard to mechanism, CDKL3 localizes in the nucleus and associates with specific cyclin to directly phosphorylate retinoblastoma (Rb) for quiescence exit. In parallel, CDKL3 prevents the ubiquitin-proteasomal degradation of cyclin-dependent kinase 4 (CDK4) by direct phosphorylation on T172 to sustain G1 phase advancement. The crucial function of CDKL3 in cancers was demonstrated both in vitro and in vivo. We also designed, synthesized, and characterized a first-in-class CDKL3-specific inhibitor, HZ1. HZ1 exhibits greater potency than CDK4/6 inhibitor in pan-cancer treatment by causing cell cycle arrest and overcomes acquired resistance to CDK4/6 inhibitor. In particular, CDKL3 has significant clinical relevance in colon cancer, and the effectiveness of HZ1 was demonstrated by murine and patient-derived cancer models. Collectively, this work presents an integrated paradigm of cancer cell cycle regulation and suggests CDKL3 targeting as a feasible approach in cancer treatment.

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Superabsorbent polymers are new functional polymeric materials that can absorb and retain liquids thousands of times their masses. This paper reviews the synthesis and modification methods of different superabsorbent polymers, summarizes the processing methods for different forms of superabsorbent polymers, and organizes the applications and research progress of superabsorbent polymers in industrial, agricultural, and biomedical industries. Synthetic polymers like polyacrylic acid, polyacrylamide, polyacrylonitrile, and polyvinyl alcohol exhibit superior water absorption properties compared to natural polymers such as cellulose, chitosan, and starch, but they also do not degrade easily. Consequently, it is often necessary to modify synthetic polymers or graft superabsorbent functional groups onto natural polymers, and then crosslink them to balance the properties of material. Compared to the widely used superabsorbent nanoparticles, research on superabsorbent fibers and gels is on the rise, and they are particularly notable in biomedical fields like drug delivery, wound dressing, and tissue engineering.

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Large DNA transfer technology has been challenged with the rapid development of large DNA assembly technology. The research and application of synthetic yeast chromosomes have been mostly limited in the assembled host itself. The mutant of KAR1 prevents nuclear fusion during yeast mating, and occasionally single chromosome can be transferred from one parental nucleus to another. Using the kar1 mutant method, four synthetic yeast chromosomes of Sc2.0 (synIII, synV, synX, synXII) were transferred to wild-type yeasts separately. SynIII was also transferred into an industrial strain Y12, resulting in an improvement of thermotolerance. Moreover, by combining abortive mating and chromosome elimination by CRISPR-Cas9, which has been reported in our previous study, we developed a strategy for consolidation of multiple synthetic yeast chromosomes. Compared to the previous pyramidal strategy using endoreduplication backcross, our method is a linear process independent of meiosis, providing a convenient path for accelerating consolidation of Sc2.0 chromosomes. Overall, the method of transfer and consolidation of synthetic yeast chromosomes by abortive mating and chromosome elimination enables a novel route that large DNA was assembled in donor yeast and then in vivo directly transferred to receptor yeasts, enriching the manipulation tools for synthetic genomics.

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BACKGROUND: Measurement uncertainty (MU) is a parameter associated with the result of a measurement that characterizes its dispersion. We report results for estimating MU following the application of a top-down procedure using only proficiency test data to establish uncertainty levels for various analytes. METHODS: Data were obtained from 142 laboratories participating in the Beijing Center for Clinical Laboratory (BCCL) proficiency testing/external quality assessment (PT/EQA) schemes. The 24-month study included six selected PT shipments to obtain estimates for 50th percentile (median) and 90th percentile MUs and to compare those estimates to usual analytic goals. The number of laboratory participants varied for each trial. The expanded uncertainty (U) was calculated using a cover factor of k=2 for a confidence interval of 95%. All reproducibility, method and laboratory biases came from the PT/EQA data. RESULTS: The median U (k=2) ranged from 3.2% (plasma sodium, indirect ion selective electrode) to 32.8% (triglycerides, free glycerol blanking) for clinical chemistry analyte means from participants in the same method group. Immunoassay analyte median U results ranged from 11.3% (CA125 tumor marker, Roche) to 33.8% (prostate-specific antigen [PSA], Abbott). The range for median U was 3.5% (red blood cell [RBC], Abx) to 30.3% (fibrinogen [FBG], other) for hematology and coagulation analytes. The MUs for most analytes satisfied quality requirements. CONCLUSIONS: The use of PT/EQA data, when available, provides an effective means for estimating uncertainties associated with quantitative measurements. Thus, medical laboratories can calculate their own MUs. Proficiency testing organizers can provide participants with an additional MU estimate using only EQA data, which may be updated at the end of each survey.

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BACKGROUND: Measurement uncertainty (MU) characterizes the dispersion of the quantity values attributed to a measurand. Although this concept was introduced to medical laboratories some years ago, not all medical researchers are familiar with it. Therefore, the evaluation and expression of MU must be highlighted. In this paper, the evaluation of MU is described by using four different approaches from different quality assessment data. METHODS: In accordance with Guide to the Expression of Uncertainty of Measurement (GUM) principles, human serum γ-glutamyltransferase (GGT) level was defined as the measurand. Main sources of MU were analyzed; individual components of MU were evaluated, followed by calculation of standard uncertainty, the combined standard uncertainty and the expanded uncertainty. RESULTS: In method 1, the median of expanded uncertainty (k=2) of GGT in lower level (65±1 U/L) was 5 U/L (9%, 95% confidence interval) and in higher level (116±2 U/L) was 8% (95% confidence interval), respectively. The results of method 2 were lower than that of method 1. There were no significant differences between the two other methods compared with the method 1. CONCLUSIONS: Three out of the four different approaches based on different quality assessment data yielded similar results. Proficiency testing or external quality assessment data used for MU evaluation can be regarded as a supplementary method in clinical laboratory.

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