Design, synthesis, and structure-activity relationship studies of 6,7-dihydro-5H-pyrrolo[1,2-b][1,2,4]triazole derivatives as necroptosis inhibitors.

The development of necroptosis inhibitors has emerged as a promising strategy to effectively mitigate necroptosis-related inflammatory diseases, neurodegenerative diseases, and cancers. In this paper, we reported a series of 6,7-dihydro-5H-pyrrolo[1,2-b][1,2,4]triazole derivatives as potent necroptosis inhibitors. The representative compound 26 displayed potent anti-necroptotic activity in both human and mouse cellular assays and exhibited potent inhibitory activity against receptor-interacting protein kinase 1 (RIPK1). In vivo pharmacokinetic studies were performed to determine the oral exposure of compound 26. Finally, molecular docking elucidated that compound 26 could effectively bind to the allosteric pocket of RIPK1 and serve as a type III inhibitor. Taken together, our findings highlighted that compound 26 represented a promising lead compound for future necroptosis inhibitor development.

Design, synthesis, and evaluation of thiazolecarboxamide derivatives as stimulator of interferon gene inhibitors.

Stimulator of interferon gene (STING) plays critical roles in the cytoplasmic DNA-sensing pathway and in the induction of inflammatory response. Aberrant cytoplasmic DNA accumulation and STING activation are implicated in numerous inflammatory and autoimmune diseases. Here, we reported the discovery of a series of thiazolecarboxamide-based STING inhibitors through a molecular planarity/symmetry disruption strategy. The privileged compound 15b significantly inhibited STING signaling and suppressed immune-inflammatory cytokine levels in both human and murine cells. In vivo experiments demonstrated 15b effectively ameliorated immune-inflammatory cytokines upregulation in MSA-2-stimulated and Trex1-D18N mice. Furthermore, compound 15b exhibited enhanced efficacy in suppressing interferon-stimulated gene 15 (ISG15), a critical positive feedback regulator of STING. Overall, compound 15b deserves further development for the treatment of STING-associated inflammatory and autoimmune diseases.

Fluorescent "AND" logic gates for simultaneous detection of thiols and protons: photophysical properties, mechanism and bioimaging of living cells.

Five fluorescent probes TP1-5 were demonstrated as two-input "AND" molecular logic gates for the detection of thiols and protons. The molecules were designed based on "thiol receptor-spacer1-fluorophore-spacer2-proton receptor" mode. The logic gates were constructed by employing maleimide, naphthalimide and morpholine (TP1-3)/N-methyl piperazine (TP4-5) as the thiol receptor, fluorophore and proton receptor, respectively. All probes show significant fluorescence enhancements upon addition of both protons and thiols. However, much weaker spectral responses were observed with the addition of only one single analyte. The fluorescence outputs, based on photoinduced electron transfer (PET) and (twisted) intramolecular charge transfer (TICT/ICT), were modulated by the proton receptor and linker. The length of spacer1 affects the responses toward thiols, whereas spacer2 influences the sensing performance toward protons. The difference between the pKa values of morpholine (∼5.80) and N-methyl piperazine (∼7.10) enables us to detect thiols in divergent pH circumstances. TP1-3 exhibit an excellent "AND" logic function for simultaneous detection of protons and thiols as well as bioimaging thiols in weakly acidic living cells. However, TP4 and TP5 are not good candidates for executing "AND" logic operation possibly due to the stronger electron donating properties and steric effect of N-methyl piperazine.

[Applied study on support vector machine (SVM) regression method in quantitative analysis with near-infrared spectroscopy].

This paper introduced the application of support vector machines(SVM) regression method based on statistics studytheory to the quantitative analysis with near-infrared (NIR) spectroscopy. Sixty-six wheat samples were used as experimental materials, and thirty-three of them were used as calibration samples. The protein contents and NIR spectra of the calibration samples were used to build SVM regression models by four different kernel functions. The protein content of the predicting samples are estimated by four different SVM regression models. All of the correlation coefficients between the estimated values by different SVM regression models and the standard chemical values of protein content by Kjeldahl's method are more than 0.97. The average absolute error is less than 0.32. To investigate the predicting effect, it is compared with PLS regression models. The result suggested that the SVM regression, which was built to estimate the protein content of wheat samples, can also be used in the quantitative analysis of real samples by NIR.