In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Input: Consider Input: Objective: To focus on the potential beneficial effects of the pleiotropic effects of dipeptidyl peptidase-4 inhibitors (DPP4is) on attenuating progression of diabetic kidney disease in reducing the long-term effect of the acute kidney injury (AKI) to chronic kidney disease (CKD) transition. , were analyzed, and patients with diabetes weaning from dialysis-requiring AKI were identified. Cox proportional hazards models and inverse-weighted estimates of the probability of treatment were used to adjust for treatment selection bias. The outcomes were incident end-stage renal disease (ESRD) and mortality, major adverse cardiovascular events, and hospitalized heart failure. Results: Of a total of 6165 patients with diabetes weaning from dialysis-requiring AKI identified, 5635 (91.4%) patients were DPP4i nonusers and 530 (8.6%) patients were DPP4i users. Compared with DPP4i nonusers, DPP4i users had a lower risk of ESRD (hazard ratio, 0.81; 95% CI, 0.70-0.94; P¼.04) and allcause mortality (hazard ratio, 0.28; 95% CI, 0.23-0.34; P<.001) after adjustments for CKD, advanced CKD, and angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker use. In contrast, the risk of major adverse cardiovascular events and hospitalized heart failure did not differ significantly between groups. Conclusion: Dipeptidyl peptidase-4 inhibitor users had a lower risk of ESRD and mortality than did nonusers among patients with diabetes after weaning from dialysis-requiring AKI. Therefore, a prospective study of AKI to CKD transitions after episodes of AKI is needed to optimally target DPP4i interventions.

Output: Patients and Methods: Data from the National Health Insurance Research Database from


Input: Consider Input: 2 The abbreviations used are: S, spike; SARS-CoV, severe acute respiratory syndrome coronavirus; MLV, murine leukemia virus; DC-SIGN, dendritic cell-specific intercellular adhesion molecule-3-gubbing non-integrin, ACE2, argiotensin I conserting enzyme 2. FIGURE 4. Introduction of alanine residues in the S2 region modulates elastase-induced virus entry mediated by SARS-CoV S. A and B, pseudotyped virion infections were performed as described for Fig. 2. Infection was induced by treatment with elastase (A) or trypsin (B). Results are presented as relative light units (RLU). Error bars represent the S.E. of three independent experiments. C, cleavage of SARS-CoV by elastase. HEK293T cells expressing the wild type (WT) or mutant SARS-CoV spike protein were treated with 50 g/ml elastase. Cell surface proteins were biotinylated and precipitated, and cleavage products of the SARS-CoV spike protein were analyzed in Western blot with an antibody recognizing the C9 tag at the C terminus of the protein.

Output: Elastase-mediated Activation of the Severe Acute Respiratory Syndrome Coronavirus Spike Protein at Discrete Sites within the S2 Domain * □ S


Input: Consider Input: Concepts are the most fundamental units of cognition in philosophy and how to learn concepts from various aspects in the real world is the main concern within the domain of conceptual knowledge presentation and processing. In order to improve efficiency and flexibility of concept learning, in this paper we discuss concept learning via granular computing from the point of view of cognitive computing. More precisely, cognitive mechanism of forming concepts is analyzed based on the principles from philosophy and cognitive psychology, including how to model concept-forming cognitive operators, define cognitive concepts and establish cognitive concept structure. Granular computing is then combined with the cognitive concept structure to improve efficiency of concept learning. Furthermore, we put forward a cognitive computing system which is the initial environment to learn composite concepts and can integrate past experiences into itself for enhancing flexibility of concept learning. Also, we investigate cognitive processes whose aims are to deal with the problem of learning one exact or two approximate cognitive concepts from a given object set, attribute set or pair of object and attribute sets.


Output: Concept learning via granular computing: A cognitive viewpoint