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Backgrounds: Tuberculoma is a granulomatous inflammatory process mimicking a neoplasm, both clinically and radiologically. Although those with an infratentorial origin are rare, this disease is still a diagnostic challenge using conventional workup. However, this disease should not be overlooked because it is essentially curable with proper diagnosis and therapy, usually, a Mycobacterium Tuberculosis (MTB) DNA test is performed. Methods: We retrospectively analyzed the clinical presentations, CSF results, and images of 11 MTB DNA positive and clinically cured cases of infratentorial tuberculoma. Results: Infratentorial tuberculoma usually deteriorated before antituberculosis treatment (ATT). Magnetic resonance imaging showed space-occupying lesions without specific features, 4 within the cerebellum and 7 within the brainstem. Evidence of systemic tuberculosis was found in only 1 case. Clinical manifestations included various combinations of focal signs and symptoms in the brain stem and cerebellum. Cerebrospinal fluid (CSF) findings were also nonspecific. The diagnoses of these cases were based on the positive tests of a nested polymerase chain reaction (N-PCR) assay. Trial therapy with antituberculous drugs resulted in clinical improvement, as documented by MRI in all patients. Conclusions: Infratentorial tuberculoma should be suspected in patients with infratentorial space-occupying lesions who live in geographic areas where tuberculosis is endemic.
In wireless sensor networks, due to the energy and resource constraints, nodes may be unwilling to forward packets for their neighbors. This can render severe deteriorations in the network performance and malfunctions of the system. To tackle such selfish behaviors and enhance the cooperation among sensors, based on reputation and energy consumption of each node, we present a utility function to punish the malicious nodes and encourage cooperation among nodes. Specifically, we firstly give a mixed strategy Nash equilibrium solution for the two nodes. Then we extend the model to multi-nodes scenario. With the unity function, each sensor’s reputation is evaluated according to its degree of cooperation. The extensive simulation results have shown the effectiveness of the mechanism, in that the cooperative behaviors are encouraged, which can ensure the normal functioning of the network system.