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Objective It is difficult to make the differential diagnosis between tuberculous meningitis (TBM) and cryptococcal meningitis (CM) when the smear is negative. The objective of this study was to create a diagnostic rule for differentiating TBM from CM in adult HIV-negative patients based on clinical and laboratory features. Methods The clinical and laboratory data of 219 adult HIV-negative patients satisfying the diagnostic criteria for tuberculous (n=100) and cryptococcal (n=119) meningitis hospitalized at the Third Affiliated Hospital of Sun Yat-Sen University during the period 2000-2009 were retrospectively analyzed. Features found to be independently predictive of tuberculous meningitis were modeled using a multivariate logistic regression to create a diagnostic rule. The performance of the diagnostic rule was assessed using a prospective test data method. Results Six factors were found to be predictive of a diagnosis of tuberculous meningitis: gender, mental disorders, vision and/or hearing damage, proteins in the cerebrospinal fluid, the total cerebrospinal fluid white cell count and the coexistence of tuberculosis in peripheral organs. The diagnostic rule developed using these features exhibited 78.0% sensitivity, 95.2% specificity, 92.9% positive predictive value and 84.4% negative predictive value. The corresponding values for the diagnostic rule were 70.0% and 88.0% using prospective test data. Conclusion Clinical and laboratory features can be helpful in the differential diagnosis of tuberculous meningitis and cryptococcal meningitis in adult HIV-negative patients.

Backgrounds Parkinson’s disease (PD) is a common age-related neurodegenerative disorder worldwide. This research aimed to investigate the effects and mechanism underlying long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in PD. Methods SK-N-SH and SK-N-BE cells were treated with MPP+ to establish the MPP+-stimulated cell model of PD, and MALAT1 expression was determined. Then, the effects of MALAT1 depletion on cell proliferation and apoptosis were determined in the MPP+-stimulated cell model of PD. Besides, the correlations between microRNA-135b-5p (miR-135b-5p) and MALAT1 or glycoprotein nonmetastatic melanoma protein B (GPNMB) in MPP+-stimulated cell model of PD were explored. Results MALAT1 was increasingly expressed and downregulation of MALAT1 promoted cell proliferation while inhibited apoptosis in MPP+-stimulated cells. Besides, miR-135b-5p was a target of MALAT1 and directly targeted to GPNMB. Further investigation indicated that suppression of MALAT1 regulated cell proliferation and apoptosis by miR-135b-5p/GPNMB axis. Conclusion Our findings reveal that MALAT1/miR-135b-5p/GPNMB axis regulated cell proliferation and apoptosis in MPP+-stimulated cell model of PD, providing a potential biomarker and therapeutic target for PD.

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