A novel implementation of in situ protein digestion supported by a graphene oxide-immobilized enzyme reactor (GO-IMER) in the MALDI imaging mass spectrometry (IMS) workflow is reported, which enables the simultaneous diagnostic identity and distribution attributes of the proteome on tissue.

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Objective. To evaluate the postoperative visual quality of cataract patients with extreme myopia after implantation of aspheric intraocular lenses (IOLs). Methods. Thirty-three eyes were enrolled in this prospectivestudy. Eighteen eyes with an axial length longer than 28 mm were included in the extreme myopia group, and the other 15 eyes were included in the nonextreme myopia group. Phacoemulsification and aspheric IOL implantation were performed. Six months after cataract surgery, best-corrected visual acuity (BCVA), contrast sensitivity, and wavefront aberrations were measured, and subjective visual quality was assessed. Results. The BCVA improved significantly after surgery for both groups, and patients in the nonextreme myopia group achieved better postoperative BCVA due to better retinal status of the eyes. The evaluation of contrast sensitivity without glare was the same in both groups, whereas patients in the nonextreme myopia group performed better at intermediate spatial frequencies under glare conditions. The two groups did not show a significant difference in high-order aberrations. With regard to subjective visual quality, the composite scores of both groups did not differ significantly. Conclusions. Aspheric IOLs provided good visual outcomes in cataract patients with extreme myopia. These patients should undergo careful evaluation to determine the maculopathy severity level before surgery.

Diabetes and high myopia as well-known high-risk factors can aggravate cataracts, yet clinical coping strategy remains a bottleneck. Metabolic analysis tends to be powerful for precisely detection and mechanism exploration since most of diseases including cataracts are accompanied by metabolic disorder. Herein, a layered binary co-ionizers assisted aqueous humor metabolic analysis tool is proposed for potentially etiological typing and detection of cataracts, including age-related cataracts (ARC), cataracts with diabetes mellitus (CDM), and cataracts with high myopia (CHM). Startlingly, taking advantage of the optimal machine learning algorithm and all metabolic fingerprints, 100% of accuracy, precision, and recall rates are achieved for arbitrary comparison between groups. Moreover, 11, 9, and 7 key metabolites with explicit identities are confirmed as markers of discriminating CDM from ARC, CHM from ARC, and CDM from CHM, and the corresponding area under the curve values of validation cohorts are 0.985, 1.000, and 1.000. Finally, the critical impact of diabetes/high myopia on cataracts is revealed by excavating the change levels and metabolic pathways of key metabolites. This work updates the insights of prevention and treatment about cataracts at metabolic level and throws out huge surprises and progresses metabolic diagnosis toward a reality.