Gaps in colonoscopy skills among endoscopists, primarily due to experience, have been identified, and solutions are critically needed. Hence, the development of a real-time robust detection system for colorectal neoplasms is considered to significantly reduce the risk of missed lesions during colonoscopy. Here, we develop an artificial intelligence (AI) system that automatically detects early signs of colorectal cancer during colonoscopy; the AI system shows the sensitivity and specificity are 97.3% (95% confidence interval [CI] = 95.9%–98.4%) and 99.0% (95% CI = 98.6%–99.2%), respectively, and the area under the curve is 0.975 (95% CI = 0.964–0.986) in the validation set. Moreover, the sensitivities are 98.0% (95% CI = 96.6%–98.8%) in the polypoid subgroup and 93.7% (95% CI = 87.6%–96.9%) in the non-polypoid subgroup; To accelerate the detection, tensor metrics in the trained model was decomposed, and the system can predict cancerous regions 21.9 ms/image on average. These findings suggest that the system is sufficient to support endoscopists in the high detection against non-polypoid lesions, which are frequently missed by optical colonoscopy. This AI system can alert endoscopists in real-time to avoid missing abnormalities such as non-polypoid polyps during colonoscopy, improving the early detection of this disease.

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The voltage-gated proton channel (Hv1/VSOP) is inhibited by Zn, of which the binding site is located in the extracellular region. We utilized attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy to examine the coordination structure by monitoring protein structural changes induced by Zn-binding. The Zn-induced difference ATR-FTIR spectra of Hv1 showed IR features that can be assigned to the histidine C5-N1 and carboxylate-COO stretches as well as amide I changes likely in α-helical peptide bonds. Analysis of vibrational frequencies indicated that the Zn is coordinated by the anionic carboxylate with monodentate mode and by the histidine at N1 (Nτ) position of the neutral imidazole form. Combined with quantum chemical calculations, the most probable coordination structure was proposed as a tetrahedral geometry with ligands of carboxylate and imidazole groups in addition to a water molecule.