Research on Quantum-Attack-Resistant Strong Forward-Secure Signature Schemes.

The security of digital signatures depends significantly on the signature key. Therefore, to reduce the impact of leaked keys upon existing signatures and subsequent ones, a digital signature scheme with strong forward security could be an effective solution. Most existing strong forward-secure digital signature schemes rely on traditional cryptosystems, which cannot effectively resist quantum attacks. By introducing lattice-based delegation technology into the key-iteration process, a two-direction and lattice-based key-iteration algorithm with strong forward security is proposed. In the proposed algorithm, a unique key pair is assigned to the signer in every period. Based on the proposed algorithm, a strong forward-secure signature scheme is further put forward, which achieves resistance to quantum attacks. Performance analysis shows that under the security assumption of the SIS problem on the lattice, the proposed strong forward-secure signature scheme is existentially unforgeable under the random oracle model. Ultimately, based on the proposed strong forward-secure signature scheme, a remote identity-authentication scheme that is resistant to quantum attacks is proposed, ensuring post-quantum security in the user-authentication process.

Qingyi granules ameliorate severe acute pancreatitis in rats by modulating the gut microbiota and serum metabolic aberrations.

CONTEXT: Qingyi granules can be used to effectively treat patients with severe acute pancreatitis (SAP). OBJECTIVE: To elucidate the role of gut microbiota-mediated metabolism in the therapeutic effects of Qingyi granules. MATERIALS AND METHODS: Sprague-Dawley rats were grouped into the sham operation, SAP model, Qingyi granule intervention (Q, 1.8 g/kg) and emodin intervention (E, 50 mg/kg) groups and observed for 24 h. H&E staining and ELISA were used for histopathological analysis and serum enzyme and cytokine assays. 16S rDNA sequencing and UHPLC-HRMS were used for gut microbiota analysis and untargeted metabolomics. RESULTS: In SAP rats, Qingyi granules decreased the pancreatic pathological score (Q, 7.4 ± 1.14; SAP, 11.6 ± 1.14, p < 0.01); serum amylase (Q, 121.2 ± 6.7; SAP, 144.3 ± 8.86, p < 0.05), lipase (Q, 566 ± 20.34; SAP, 656.7 ± 29.32, p < 0.01), and diamineoxidase (Q, 492.8 ± 26.08; SAP, 566.1 ± 26.83, p < 0.05) activities; and IL-1ß (Q, 29.48 ± 0.88; SAP, 36.17 ± 1.88, p < 0.01), IL-6 (Q, 112.2 ± 3.57; SAP, 128.9 ± 9.09, p < 0.05) and TNF-α (Q, 215.3 ± 8.67; SAP, 266.4 ± 28.03, p < 0.05) levels. SAP induced Helicobacter and Lactobacillus overgrowth and suppressed Romboutsia and Allobaculum growth and caused aberrations in bacterial metabolites, which were partly reversed by Qingyi granules. DISCUSSION AND CONCLUSIONS: Qingyi granules can modulate the gut microbiota and metabolic abnormalities to ameliorate SAP. Multi-omics approaches allow systematic study of the pharmacological mechanisms of compound prescriptions for critical illnesses.

Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer.

Pancreatic cancer (PC) is burdened with a low 5-year survival rate and high mortality due to a severe lack of early diagnosis methods and slow progress in treatment options. To improve clinical diagnosis and enhance the treatment effects, we applied metabolomics using ultra-high-performance liquid chromatography with a high-resolution mass spectrometer (UHPLC-HRMS) to identify and validate metabolite biomarkers from paired tissue samples of PC patients. Results showed that the metabolic reprogramming of PC mainly featured enhanced amino acid metabolism and inhibited sphingolipid metabolism, which satisfied the energy and biomass requirements for tumorigenesis and progression. The altered metabolism results were confirmed by the significantly changed gene expressions in PC tissues from an online database. A metabolites biomarker panel (six metabolites) was identified for the differential diagnosis between PC tumors and normal pancreatic tissues. The panel biomarker distinguished tumors from normal pancreatic tissues in the discovery group with an area under the curve (AUC) of 1.0 (95%CI, 1.000-1.000). The biomarker panel cutoff was 0.776. In the validation group, an AUC of 0.9000 (95%CI = 0.782-1.000) using the same cutoff, successfully validated the biomarker signature. Moreover, this metabolites panel biomarker had a great capability to predict the overall survival (OS) of PC. Taken together, this metabolomics method identifies and validates metabolite biomarkers that can diagnose the onsite progression and prognosis of PC precisely and sensitively in a clinical setting. It may also help clinicians choose proper therapeutic interventions for different PC patients and improve the survival of PC patients.

Gut Microbiome and the Role of Metabolites in the Study of Graves' Disease.

Graves' disease (GD) is an autoimmune thyroid disease (AITD), which is one of the most common organ-specific autoimmune disorders with an increasing prevalence worldwide. But the etiology of GD is still unclear. A growing number of studies show correlations between gut microbiota and GD. The dysbiosis of gut microbiota may be the reason for the development of GD by modulating the immune system. Metabolites act as mediators or modulators between gut microbiota and thyroid. The purpose of this review is to summarize the correlations between gut microbiota, microbial metabolites and GD. Challenges in the future study are also discussed. The combination of microbiome and metabolome may provide new insight for the study and put forward the diagnosis, treatment, prevention of GD in the future.