Exact, E=0, Solutions for General Power-Law Potentials. I. Classical Orbits

For zero energy, $E=0$, we derive exact, classical solutions for {\em all} power-law potentials, $V(r)=-\gamma/r^\nu$, with $\gamma>0$ and $-\infty <\nu<\infty$. When the angular momentum is non-zero, these solutions lead to the orbits $\r(t)= [\cos \mu (\th(t)-\th_0(t))]^{1/\mu}$, for all $\mu \equiv \nu/2-1 \ne 0$. When $\nu>2$, the orbits are bound and go through the origin. This leads to discrete discontinuities in the functional dependence of $\th(t)$ and $\th_0(t)$, as functions of $t$, as the orbits pass through the origin. We describe a procedure to connect different analytic solutions for successive orbits at the origin. We calculate the periods and precessions of these bound orbits, and graph a number of specific examples. Also, we explain why they all must violate the virial theorem. The unbound orbits are also discussed in detail. This includes the unusual orbits which have finite travel times to infinity and also the special $\nu = 2$ case.Comment: LaTeX, 27 pages with 12 figures available from the authors or can be generated from Mathematica instructions at end of the fil

Th17 responses are not altered by natural exposure to seasonal allergens in pollen-sensitive patients

Background: Allergic rhinitis affects 10–30 % of the global population and this number is likely to increase in the forthcoming years. Moreover, it commonly co-exists with allergic asthma as a chronic allergic respiratory syndrome. While the involvement of Th2 cells in allergy is well understood, alterations of pro-inflammatory Th17 responses remain poorly characterized. The aim of our study was to determine whether natural seasonal allergen exposure causes changes in T cell subset characteristics in patients with allergic rhinitis and asthma. Methods: Sixteen patients with allergic rhinitis/atopic asthma (9M, 7F; age 31.8 ± 12.1) and 16 healthy controls were recruited into the study (9M, 7F; age 31.2 ± 5.3). Blood samples were collected from the patients 1–3 months before pollen season (visit 1), within 7 days of the appearance of pollen/initiation of allergic symptoms (visit 2) and 2 weeks after visit 2 following the introduction of symptomatic treatment with antihistamines (visit 3). Flow cytometry was used to assess major T cell subsets (naïve, central memory, effector memory and CD45RA+ effector) and key T cell cytokine production (IFNγ, IL-17A, TNF and IL-4) using intracellular staining. Data were analyzed using repeated measures ANOVA and paired t test. Results: As expected, an increase in the percentage of IL‐4+ CD4+ cells was observed during natural pollen exposure in patients with allergic respiratory syndrome. No significant changes were observed in the production of other cytokines, including Th17 cells, which tended to be lower than in the control population but unchanged during pollen exposure. Introduction of antihistamine treatment led to only moderate changes in cytokine production from CD4 and CD8 T cells. Selective changes in CD8+ T cells were observed during natural pollen exposure including a decrease in transient cells (with features of CD45RA+ and CD45RO+ cells) and a decrease in the percentage of central memory cells in the peripheral circulation. Within the CD4 cell group the total percentage of CD45RA positive CD4 cells was increased during pollen exposure. Conclusions: Th1 and Th17 responses are not altered during pollen season but allergen exposure affects T cell activation and memory cell status in patients with allergic respiratory syndrome

Machine learning in anesthesiology:Detecting adverse events in clinical practice

The credibility of threshold-based alarms in anesthesia monitors is low and most of the warnings they produce are not informative. This study aims to show that Machine Learning techniques have a potential to generate meaningful alarms during general anesthesia without putting constraints on the type of procedure. Two distinct approaches were tested - Complication Detection and Anomaly Detection. The former is a generic supervised learning problem and for this a simple feed-forward Neural Network performed best. For the latter, we used an Encoder-Decoder Long Short-Term Memory architecture that does not require a large manually-labeled dataset. We show this approach to be more flexible and in the spirit of Explainable Artificial Intelligence, offering greater potential for future improvement

Hyperandrogenism and Metabolic Syndrome Are Associated With Changes in Serum-Derived microRNAs in Women With Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) remains one of the most common endocrine disorder in premenopausal women with an unfavorable metabolic risk profile. Here, we investigate whether biochemical hyperandrogenism, represented by elevated serum free testosterone, resulted in an aberrant circulating microRNA (miRNAs) expression profile and whether miRNAs can identify those PCOS women with metabolic syndrome (MetS). Accordingly, we measured serum levels of miRNAs as well as biochemical markers related to MetS in a case-control study of 42 PCOS patients and 20 Controls. Patients were diagnosed based on the Rotterdam consensus criteria and stratified based on serum free testosterone levels (≥0.034 nmol/l) into either a normoandrogenic (n = 23) or hyperandrogenic (n = 19) PCOS group. Overall, hyperandrogenic PCOS women were more insulin resistant compared to normoandrogenic PCOS women and had a higher prevalence of MetS. A total of 750 different miRNAs were analyzed using TaqMan Low-Density Arrays. Altered levels of seven miRNAs (miR-485-3p, -1290, -21-3p, -139-3p, -361-5p, -572, and -143-3p) were observed in PCOS patients when compared with healthy Controls. Stratification of PCOS women revealed that 20 miRNAs were differentially expressed between the three groups. Elevated serum free testosterone levels, adjusted for age and BMI, were significantly associated with five miRNAs (miR-1290, -20a-5p, -139-3p, -433-3p, and -361-5p). Using binary logistic regression and receiver operating characteristic curves (ROC), a combination panel of three miRNAs (miR-361-5p, -1225-3p, and -34-3p) could correctly identify all of the MetS cases within the PCOS group. This study is the first to report comprehensive miRNA profiling in different subgroups of PCOS women with respect to MetS and suggests that circulating miRNAs might be useful as diagnostic biomarkers of MetS for a different subset of PCOS