ABSTRACT
Building nanostructures one-by-one requires precise control of single molecules over many manipulation steps. The ideal scenario for machine learning algorithms is complex, repetitive, and time-consuming. Here, we show a reinforcement learning algorithm that learns how to control a single dipolar molecule in the electric field of a scanning tunneling microscope. Using about 2250 iterations to train, the algorithm learned to manipulate the molecule toward specific positions on the surface. Simultaneously, it generates physical insights into the movement as well as orientation of the molecule, based on the position where the electric field is applied relative to the molecule. This reveals that molecular movement is strongly inhibited in some directions, and the torque is not symmetric around the dipole moment.
ABSTRACT
BACKGROUND: Since the turn of the millennium there has been an alarming increase in the incidence and severity of clostridium difficile infections. Stopping medication with the triggering antibiotic and switching to a recommended antibiotic leads to healing up in 80%. However, patients who relapse have a 40% risk of an additional relapse and those with 2 or more episodes face a 60% risk. Fecal microbiota transplantation (FMT) is a new therapeutic option. Up to now there only exist two randomized studies (University of Amsterdam and the Massachusetts General Hospital in Boston). METHOD: Data from 16 patients with recurrent clostridium difficile infection who had undergone FMT at a local hospital in the city of Bremen, Germany, were reviewed and compared to the results of the 2 randomized studies. RESULTS: 11 out of 16 patients got cured after the first FMT (68.75%). The remaining 5 patients received a second FMT, with cure in 3 patients. The overall response rate was 14 from 16 patients (87.5%). CONCLUSIONS: In comparison to the response rates of the University of Amsterdam (81.3% after the first and 93.8% after the second FMT) and of the Massachusetts General Hospital in Boston (70% after the first and 90% after the second FMT) we received slightly worse results. But, treatment of notably older patients and intensive care patients in our group explain these findings well. Therefore, we advocate a wide use of FMT for the treatment of recurrent clostridium difficile colitis in non-university hospitals.
Subject(s)
Clostridioides difficile , Enterocolitis, Pseudomembranous/therapy , Fecal Microbiota Transplantation , Feces/microbiology , Aged , Aged, 80 and over , Colonoscopy , Conscious Sedation , Female , Humans , Male , Middle Aged , Recurrence , Retreatment , Retrospective StudiesABSTRACT
Polycyclic aromatic hydrocarbons (PAH) are products of the incomplete combustion of organic materials and, therefore, occur ubiquitously in the environment and also in tobacco smoke. Since some PAH have been classified as carcinogens, it is important to have access to suitable analytical methods for biomarkers of exposure to this class of compounds. Past experience has shown that measuring a profile of PAH metabolites is more informative than metabolites of a single PAH. Assessment of environmental and smoking-related exposure levels requires analytical methods with high sensitivity and specificity. In addition, these methods should be fast enough to allow high throughput. With these pre-conditions in mind, we developed and validated a high-performance liquid chromatographic method with tandem mass spectrometric detection (LC-MS/MS) for the determination of phenolic metabolites of naphthalene, fluorene, phenanthrene and pyrene in urine of smokers and non-smokers. Sample work-up comprised enzymatic hydrolysis of urinary conjugates and solid-phase extraction on C18 cartridges. The method showed good specificity, sensitivity, and accuracy for the intended purpose and was also sufficiently rapid with a sample throughput of about 350 per week. Application to urine samples of 100 smokers and 50 non-smokers showed significant differences between both groups for all measured PAH metabolites, and strong correlations with markers of daily smoke exposure in smoker urine. Urinary levels were in good agreement with previously reported data using different methodologies. In conclusion, the developed LC-MS/MS method is suitable for the quantification of phenolic PAH metabolites of naphthalene, fluorene, phenanthrene, and pyrene in smoker and non-smoker urine.