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.
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Question: Collagen-induced arthritis is a B cell-mediated autoimmune disease. Recently published studies have demonstrated that in some rare cases pathogens can confer protection from autoimmunity. Trypanosoma brucei parasites are tsetse fly transmitted extracellular protozoans causing sleeping sickness disease in humans and Nagana in livestock in sub-Saharan endemic areas. In the past, we demonstrated that trypanosome infections impair B cell homeostasis and abolish vaccine-induced protection against unrelated antigens. Hence, here we hypothesized that trypanosome infection can affect the onset of CIA by specifically dampening specific B-cell responses and type II collagen antibody titers in DBA/1 prone mice. We observed a substantial delay in the onset of collagen-induced arthritis in T. brucei-infected DBA/1 mice that correlates with a drastic decrease of type II collagen titers of the different IgG isotypes in the serum. Treatment of infected mice with Berenil, a trypanocidal drug, restored the development of CIA-associated clinical symptoms. Interestingly, these data were confirmed by the challenge of immunized DBA/1 prone mice with T. brucei-infected tsetse flies. Together, these results demonstrate that T. brucei infection is impairing the maintenance of the antigen specific plasma B cell pool driving the development of CIA in DBA/1 prone mice.

Answer: Experimental African Trypanosome Infection by Needle Passage or Natural Tsetse Fly Challenge Thwarts the Development of Collagen-Induced Arthritis in DBA/1 Prone Mice via an Impairment of Antigen Specific B Cell Autoantibody Titers


Question: Background: We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, using artificial neural network (ANN) method. The query protein sequence is dissected into overlapping short sequence segments. Ten different physicochemical features describe each amino acid; therefore nine residues long segment is represented as a point in a 90 dimensional space. The database of sequence segments with confirmed by experiments post-translational modification sites are used for training a set of ANNs. The efficiency of the classification for each type of modification and the prediction power of the method is estimated here using recall (sensitivity), precision values, the area under receiver operating characteristic (ROC) curves and leave-one-out tests (LOOCV). The significant differences in the performance for differently optimized neural networks are observed, yet the AMS 3.0 tool integrates those heterogeneous classification schemes into the single consensus scheme, and it is able to boost the precision and recall values independent of a PTM type in comparison with the currently available state-of-the art methods. The standalone version of AMS 3.0 presents an efficient way to indentify post-translational modifications for whole proteomes. The training datasets, precompiled binaries for AMS 3.0 tool and the source code are available at Additional file 1 Supplementary materials for the publication. Supplementary.xls contains detailed results of training and testing of AMS 3.0 tool in MS Excel file format. Additional file 2 PTM predictor software with training data. PTM_Archive.tar.gz includes the predictor software binaries together with all trained ANNs in tar.gz compressed form.

Answer: AMS 3.0: prediction of post-translational modifications


Question: Muscle wasting is one of the main features of cancer cachexia, a multifactorial syndrome frequently occurring in oncologic patients. The onset of cachexia is associated with reduced tolerance and response to antineoplastic treatments, eventually leading to clinical conditions that are not compatible with survival. Among the mechanisms underlying cachexia, protein and energy dysmetabolism play a major role. In this regard, several potential treatments have been proposed, mainly on the basis of promising results obtained in preclinical models. However, at present, no treatment yet reached validation to be used in the clinical practice, although several drugs are currently tested in clinical trials for their ability to improve muscle metabolism in cancer patients. Along this line, the results obtained in both experimental and clinical studies clearly show that cachexia can be effectively approached by a multidirectional strategy targeting nutrition, inflammation, catabolism, and inactivity at the same time. In the present study, approaches aimed to modulate muscle metabolism in cachexia will be reviewed.

Answer:
Modulating Metabolism to Improve Cancer-Induced Muscle Wasting