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: Background: The telomere biology disorders (TBDs) include a range of multisystem diseases characterized by mucocutaneous symptoms and bone marrow failure. In dyskeratosis congenita (DKC), the clinical features of TBDs stem from the depletion of crucial stem cell populations in highly proliferative tissues, resulting from abnormal telomerase function. Due to the wide spectrum of clinical presentations and lack of a conclusive laboratory test it may be challenging to reach a clinical diagnosis, especially if patients lack the pathognomonic clinical features of TBDs. Methods: Clinical sequencing was performed on a cohort of patients presenting with variable immune phenotypes lacking molecular diagnoses. Hypothesis-free whole-exome sequencing (WES) was selected in the absence of compelling diagnostic hints in patients with variable immunological and haematological conditions. In four patients belonging to three families, we have detected five novel variants in known TBD-causing genes (DKC1, TERT and RTEL1). In addition to the molecular findings, they all presented shortened blood cell telomeres. These findings are consistent with the displayed TBD phenotypes, addressing towards the molecular diagnosis and subsequent clinical follow-up of the patients. Conclusions: Our results strongly support the utility of WES-based approaches for routine genetic diagnostics of TBD patients with heterogeneous or atypical clinical presentation who otherwise might remain undiagnosed.

Output: Diagnostics of rare disorders: whole-exome sequencing deciphering locus heterogeneity in telomere biology disorders


Input: Consider Input: Viral infection induces innate immunity and apoptosis. Apoptosis is an effective means to sacrifice virus-infected host cells and therefore restrict the spread of pathogens. However, the underlying mechanisms of this process are still poorly understood. Here, we show that the mitochondrial antiviral signaling protein (MAVS/VISA/Cardif/IPS-1) is critical for SeV (Sendai virus)-induced apoptosis. MAVS specifically activates c-Jun N-terminal kinase 2 (JNK2) but not other MAP kinases. Jnk22/2 cells, but not Jnk12/2 cells, are unable to initiate virus-induced apoptosis and SeV further fails to trigger apoptosis in MAPK kinase 7 (MKK7) knockout (Mkk72/2) cells. Mechanistically, MAVS recruits MKK7 onto mitochondria via its 3D domain, which subsequently phosphorylates JNK2 and thus activates the apoptosis pathway. Consistently, Jnk22/2 mice, but not Jnk12/2 mice, display marked inflammatory injury in lung and liver after viral challenge. Collectively, we have identified a novel signaling pathway, involving MAVS-MKK7-JNK2, which mediates virus-induced apoptosis and highlights the indispensable role of mitochondrial outer membrane in host defenses.

Output: MAVS-MKK7-JNK2 Defines a Novel Apoptotic Signaling Pathway during Viral Infection


Input: Consider Input: Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI) networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of ''biologically central (BC)'' genes (i.e., their protein products), such as those involved in aging, cancer, infectious diseases, or signaling and drugtargeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network. To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC) role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs) in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its ''spine'' that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks.


Output: Dominating Biological Networks