Five-year impact of repeated praziquantel treatment on subclinical morbidity due to Schistosoma japonicum in China

We report the 5-year impact (1996-2001) of repeated praziquantel chemotherapy on subclinical morbidity related to Schistosoma japonicum infection. We repeated stool examinations and hepatosplenic ultrasonography in a cohort of 120 individuals living on an island with endemic infection in Dongting Lake, China. Prevalence of schistosome infection fell by 43% and intensity (geometric mean eggs per gram) declined by 80% over the 5 years. However, transmission persisted at a dangerously high rate of 13% per year for re-infection or new infection in the cohort. The prevalence of left-lobe enlargement and dilated portal vein fell significantly (P 0.05). However, endpoint infection was even more strongly associated with left-lobe enlargement (57% versus 15%, P < 0.01). The proportions of subjects with improved parenchymal and periportal fibrosis were much higher than the proportions of subjects that progressed (P < 0.05). Reduction of prevalence and intensity of infection, and improvement of subclinical morbidity, were benefits of repeated treatments. Further research is needed to understand why some patients developed fibrosis despite substantial reductions in egg counts and to evaluate the functional importance of residual subclinical morbidity after chemotherapy-based control in the lake and marshland area of Chin

Two-year impact of praziquantel treatment for Schistosoma japonicum infection in China: re-infection, subclinical disease and fibrosis marker measurements

We studied a community cohort of 193 individuals exposed to endemic Schistosoma japonicum infection in the Dongting Lake region of China to assess subclinical morbidity and the 2-year benefit of curative therapy (praziquantel) administered in 1996. Prevalence and intensity of S. japonicum infection before treatment were 28% and 192 eggs per gram faeces (epg), respectively. Two years after cure, 22% of the cohort were reinfected, but with a lighter intensity (67 epg). Sixty-four subjects (37%) showed significant improvement in ultrasound parenchyma images after treatment and 51 subjects (54%) showed significant improvement of periportal fibrosis. Left-lobe enlargement also reversed (P 0·05). The serum levels of laminin and collagen IV associated with reinfection and intensity and hyaluronic acid levels correlated with ultrasound findings (P < 0·01). Overall, treatment induced a marked decrease in subclinical hepatosplenic morbidity attributable to S. japonicum although low-intensity re-infection after treatment remained relatively frequent. Stratified analysis and logistic models evaluated potential confounding factors for assessment of treatment effects on hepatic fibrosis. S. japonicum infection and moderate-heavy alcohol intake interacted: improvement in parenchymal morbidity was impeded among drinkers (P < 0·05). Chemotherapy focused on at-risk residents controls prevalent subclinical hepatic fibrosis but re-infection indicates the need for complementary control strategie

Subspecies typing of Streptococcus agalactiae based on ribosomal subunit protein mass variation by MALDI-TOF MS

Background: A ribosomal subunit protein (rsp)-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method was developed for fast subspecies-level typing of Streptococcus agalactiae (Group B Streptococcus, GBS), a major cause of neonatal sepsis and meningitis. Methods: A total of 796 GBS whole genome sequences, covering the genetic diversity of the global GBS population, were used to in silico predict molecular mass variability of 28 rsp and to identify unique rsp mass combinations, termed “rsp-profiles”. The in silico established GBS typing scheme was validated by MALDI-TOF MS analysis of GBS isolates at two independent research sites in Europe and South East Asia. Results: We identified in silico 62 rsp-profiles, with the majority (>80%) of the 796 GBS isolates displaying one of the six rsp-profiles 1-6. These dominant rsp-profiles classify GBS strains in high concordance with the core-genome based phylogenetic clustering. Validation of our approach by in-house MALDI-TOF MS analysis of 248 GBS isolates and external analysis of 8 GBS isolates showed that across different laboratories and MALDI-TOF MS platforms, the 28 rsp were detected reliably in the mass spectra, allowing assignment of clinical isolates to rsp-profiles at high sensitivity (99%) and specificity (97%). Our approach distinguishes the major phylogenetic GBS genotypes, identifies hyper-virulent strains, predicts the probable capsular serotype and surface protein variants and distinguishes between GBS genotypes of human and animal origin. Conclusion: We combine the information depth of whole genome sequences with the highly cost efficient, rapid and robust MALDI-TOF MS approach facilitating high-throughput, inter-laboratory, large-scale GBS epidemiological and clinical studies based on pre-defined rsp-profiles

Bayesian data integration and variable selection for pan‐cancer survival prediction using protein expression data

Accurate prognostic prediction using molecular information is a challenging area of research, which is essential to develop precision medicine. In this paper, we develop translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients. There are considerable statistical and computational challenges due to the large dimension of the problems. Furthermore, data are available for different tumor types; hence data integration for various tumors is desirable. Having censored survival outcomes escalates one more level of complexity in the inferential procedure. We develop Bayesian hierarchical survival models, which accommodate all the challenges mentioned here. We use the hierarchical Bayesian accelerated failure time model for survival regression. Furthermore, we assume sparse horseshoe prior distribution for the regression coefficients to identify the major proteomic drivers. We borrow strength across tumor groups by introducing a correlation structure among the prior distributions. The proposed methods have been used to analyze data from the recently curated “The Cancer Proteome Atlas” (TCPA), which contains reverse‐phase protein arrays–based high‐quality protein expression data as well as detailed clinical annotation, including survival times. Our simulation and the TCPA data analysis illustrate the efficacy of the proposed integrative model, which links different tumors with the correlated prior structures.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154486/1/biom13132_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154486/2/biom13132.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154486/3/biom13132-sup-0003-supmat.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154486/4/biom13132-sup-0002-supplementary-v6-22Jul2019.pd

Match-making for posaconazole through systems thinking

Currently available drugs for Chagas’ disease are limited by toxicity and low efficacy in the chronic stage. Posaconazole, the most advanced new anti-chagasic drug candidate, did not fully confirm its initial potential in a Phase II clinical trial for chronic Chagas’ disease. Given that posaconazole is highly active against Trypanosoma cruzi in vitro, and was very well tolerated in clinical trials, it should not be abandoned. Rather, a combination therapy may provide a highly promising outlook. Systems-scale approaches facilitate the hunt for a combination partner for posaconazole, which acts by blocking sterol biosynthesis. Mounting evidence suggests the functional interactions between sterols and sphingolipids in vivo. Here, we propose combining sterol and sphingolipid biosynthesis inhibitors to advance drug development in Chagas’ disease