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Purpose Methods Results Conclusion To develop and validate an effective nomogram for predicting poor response to orthokeratology.Myopic children (aged 8–15 years) treated with orthokeratology between February 2018 and January 2022 were screened in four hospitals of different tiers (i.e. municipal and provincial) in China. Potential predictors included 32 baseline clinical variables. Nomogram for the outcome (1‐year axial elongation ≥0.20 mm: poor response; <0.20 mm: good response) was computed from a logistic regression model with the least absolute shrinkage and selection operator. The data from the First Affiliated Hospital of Chengdu Medical College were randomly assigned (7:3) to the training and validation cohorts. An external cohort from three independent multicentre was used for the model test. Model performance was assessed by discrimination (the area under curve, AUC), calibration (calibration plots) and utility (decision curve analysis).Between January 2022 and March 2023, 1183 eligible subjects were screened from the First Affiliated Hospital of Chengdu Medical College, then randomly divided into training (n = 831) and validation (n = 352) cohorts. A total of 405 eligible subjects were screened in the external cohort. Predictors included in the nomogram were baseline age, spherical equivalent, axial length, pupil diameter, surface asymmetry index and parental myopia (p < 0.05). This nomogram demonstrated excellent calibration, clinical net benefit and discrimination, with the AUC of 0.871 (95% CI 0.847–0.894), 0.863 (0.826–0.901) and 0.817 (0.777–0.857) in the training, validation and external cohorts, respectively. An online calculator was generated for free access (http://39.96.75.172:8182/#/nomogram).The nomogram provides accurate individual prediction of poor response to overnight orthokeratology in Chinese myopic children. [ABSTRACT FROM AUTHOR]

Several lines of evidence suggest that exosomal miRNAs are potential biomarkers for cancer monitoring. An urgent need remains for the in situ detection of exosomal miRNAs at low concentrations without destroying the exosome structure. In the present study, a novel sensitive exosomal miR-1246 in situ detection strategy has been developed by integrating the CRISPR/Cas13a system with the formation of hybrids between exosomes and cationic liposomes. The liposomes were loaded with CRISPR/Cas13a, CRISPR RNA (crRNA), and RNA reporter probes. In the presence of exosomes, the liposome–exosome hybrids were formed through electrostatic interactions, and CRISPR/Cas13a was activated to cleave the reporter probes by exosomal miR-1246. The acquired fluorescence signal showed a linear response to the logarithm of MCF-7 exosome concentrations, indicating a quantitative response to exosomal miR-1246. The regression equation is y = 5021 log C − 9976 (R2 = 0.9985) with a limit of detection of 3 × 102 particles per mL. This strategy could not only be used to detect serum exosomal miR-1246 in breast cancer patients but also to distinguish early form advanced disease. This strategy can be exploited in future exosomal miRNA analyses. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.comnet.2006.05.003 Byline: Wenting Tang (a), Yun Fu (b), Ludmila Cherkasova (a), Amin Vahdat (b) Keywords: Streaming media server workload; Synthetic workload generator; Media access patterns; Temporal and static properties; Non-stationary popularity; Zipf-Mandelbrot law; File life span; Modeling Abstract: Currently, Internet hosting centers and content distribution networks leverage statistical multiplexing to meet the performance requirements of a number of competing hosted network services. Developing efficient resource allocation mechanisms for such services requires an understanding of both the short-term and long-term behavior of client access patterns to these competing services. At the same time, streaming media services are becoming increasingly popular, presenting new challenges for designers of shared hosting services. These new challenges result from fundamentally new characteristics of streaming media relative to traditional web objects, principally different client access patterns and significantly larger computational and bandwidth overhead associated with a streaming request. To understand the characteristics of these new workloads we use two long-term traces of streaming media services to develop MediSyn, a publicly available streaming media workload generator. In summary, this paper makes the following contributions: (i) we propose a framework for modeling long-term behavior of network services by capturing the process of file introduction, non-stationary popularity of media accesses, file duration, encoding bit rate, and session duration. (ii) We propose a variety of practical models based on the study of the two workloads. (iii) We develop an open-source synthetic streaming service workload generator to demonstrate the capability of our framework to capture the models. Author Affiliation: (a) Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA 94303, United States (b) Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States Article History: Received 28 May 2004; Revised 27 February 2006; Accepted 2 May 2006 Article Note: (miscellaneous) Responsible Editor: U. Krieger