Deep Point Correlation Design

Designing point patterns with desired properties can require substantial effort, both in hand-crafting coding and mathematical derivation. Retaining these properties in multiple dimensions or for a substantial number of points can be challenging and computationally expensive. Tackling those two issues, we suggest to automatically generate scalable point patterns from design goals using deep learning. We phrase pattern generation as a deep composition of weighted distance-based unstructured filters. Deep point pattern design means to optimize over the space of all such compositions according to a user-provided point correlation loss, a small program which measures a pattern’s fidelity in respect to its spatial or spectral statistics, linear or non-linear (e. g., radial) projections, or any arbitrary combination thereof. Our analysis shows that we can emulate a large set of existing patterns (blue, green, step, projective, stair, etc.-noise), generalize them to countless new combinations in a systematic way and leverage existing error estimation formulations to generate novel point patterns for a user-provided class of integrand functions. Our point patterns scale favorably to multiple dimensions and numbers of points: we demonstrate nearly 10 k points in 10-D produced in one second on one GPU. All the resources (source code and the pre-trained networks) can be found at https://sampling.mpi-inf.mpg.de/deepsampling.html

Cryo-EM structures reveal intricate Fe-S cluster arrangement and charging in Rhodobacter capsulatus formate dehydrogenase

Metal-containing formate dehydrogenases (FDH) catalyse the reversible oxidation of formate to carbon dioxide at their molybdenum or tungsten active site. They display a diverse subunit and cofactor composition, but structural information on these enzymes is limited. Here we report the cryo-electron microscopic structures of the soluble Rhodobacter capsulatus FDH (RcFDH) as isolated and in the presence of reduced nicotinamide adenine dinucleotide (NADH). RcFDH assembles into a 360 kDa dimer of heterotetramers revealing a putative interconnection of electron pathway chains. In the presence of NADH, the RcFDH structure shows charging of cofactors, indicative of an increased electron load

GlowGAN: Unsupervised Learning of HDR Images from LDR Images in the Wild

Most in-the-wild images are stored in Low Dynamic Range (LDR) form, servingas a partial observation of the High Dynamic Range (HDR) visual world. Despitelimited dynamic range, these LDR images are often captured with differentexposures, implicitly containing information about the underlying HDR imagedistribution. Inspired by this intuition, in this work we present, to the bestof our knowledge, the first method for learning a generative model of HDRimages from in-the-wild LDR image collections in a fully unsupervised manner.The key idea is to train a generative adversarial network (GAN) to generate HDRimages which, when projected to LDR under various exposures, areindistinguishable from real LDR images. The projection from HDR to LDR isachieved via a camera model that captures the stochasticity in exposure andcamera response function. Experiments show that our method GlowGAN cansynthesize photorealistic HDR images in many challenging cases such aslandscapes, lightning, or windows, where previous supervised generative modelsproduce overexposed images. We further demonstrate the new application ofunsupervised inverse tone mapping (ITM) enabled by GlowGAN. Our ITM method doesnot need HDR images or paired multi-exposure images for training, yet itreconstructs more plausible information for overexposed regions thanstate-of-the-art supervised learning models trained on such data.<br

Helium metastable species generation in atmospheric pressure RF plasma jets driven by tailored voltage waveforms in mixtures of He and N2

Spatially resolved tunable diode-laser absorption measurements of the absolute densities of He-I (23S1) metastables in a micro atmospheric pressure plasma jet operated in He/N2 and driven by 'peaks'- and 'valleys'-type tailored voltage waveforms are presented. The measurements are performed at different nitrogen admixture concentrations and peak-to-peak voltages with waveforms that consist of up to four consecutive harmonics of the fundamental frequency of 13.56 MHz. Comparisons of the measured metastable densities with those obtained from particle-in-cell/Monte Carlo collision simulations show a good quantitative agreement. The density of helium metastables is found to be significantly enhanced by increasing the number of consecutive driving harmonics. Their generation can be further optimized by tuning the peak-to-peak voltage amplitude and the concentration of the reactive gas admixture. These findings are understood based on detailed fundamental insights into the spatio-temporal electron dynamics gained from the simulations, which show that voltage waveform tailoring allows to control the electron energy distribution function to optimize the metastable generation. A high degree of correlation between the metastable creation rate and the electron impact excitation rate from the helium ground state into the He-I ((3s)3S1) level is observed for some conditions which may facilitate an estimation of the metastable densities based on phase resolved optical emission spectroscopy measurements of the 706.5 nm He-I line originating from the above level and metastable density values at proper reference conditions

Socioeconomic predictors and consequences of depression among primary care attenders with non-communicable diseases in the Western Cape, South Africa:Cohort study within a randomised trial

Background: Socioeconomic predictors and consequences of depression and its treatment were investigated in 4393 adults with specified non-communicable diseases attending 38 public sector primary care clinics in the Eden and Overberg districts of the Western Cape, South Africa.   Methods: Participants were interviewed at baseline in 2011 and 14 months later, as part of a randomised controlled trial of a guideline-based intervention to improve diagnosis and management of chronic diseases. The 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) was used to assess depression symptoms, with higher scores representing more depressed mood. Results: Higher CESD-10 scores at baseline were independently associated with being less educated (p=0.004) and having lower income (p=0.003). CESD-10 scores at follow-up were higher in participants with less education (p=0.010) or receiving welfare grants (p=0.007) independent of their baseline scores. Participants with CESD-10 scores of 10 or more at baseline (56% of all participants) had 25% higher odds of being unemployed at follow-up (p=0.016), independently of baseline CESD-10 score and treatment status. Among participants with baseline CESD-10 scores of 10 or more, antidepressant medication at baseline was independently more likely in participants who had more education (p=0.002), higher income (p<0.001), or were unemployed (p=0.001). Antidepressant medication at follow up was independently more likely in participants with higher income (p=0.023), and in clinics with better access to pharmacists (p=0.053) and off-site drug delivery (p=0.013).  Conclusions: Socioeconomic disadvantage appears to be both a cause and consequence of depression, and may also be a barrier to treatment. There are opportunities for improving the prevention, diagnosis and treatment of depression in primary care in inequitable middle income countries like South Africa.  Trial registration: The trial is registered with Current Controlled Trials (ISRCTN20283604) and the Office for Human Research Protections Database (IRB00001938, FWA00001637)

Purification, characterization, and cloning of a bifunctional molybdoenzyme with hydratase and alcohol dehydrogenase activity

A bifunctional hydratase/alcohol dehydrogenase was isolated from the cyclohexanol degrading bacterium Alicycliphilus denitrificans DSMZ 14773. The enzyme catalyzes the addition of water to α,β-unsaturated carbonyl compounds and the subsequent alcohol oxidation. The purified enzyme showed three subunits in SDS gel, and the gene sequence revealed that this enzyme belongs to the molybdopterin binding oxidoreductase family containing molybdopterins, FAD, and iron-sulfur clusters

Time series clustering of T cell subsets dissects heterogeneity in immune reconstitution and clinical outcomes among MUD-HCT patients receiving ATG or PTCy

IntroductionAnti-T-lymphocyte globulin (ATG) or post-transplant cyclophosphamide (PTCy) prevent graft-versus-host disease (GVHD) after hematopoietic cell transplantation (HCT), yet individual patients benefit differentially.MethodsGiven the sparse comparative data on the impact of cellular immune reconstitution in this setting, we studied flow cytometry and clinical outcomes in 339 recipients of 10/10 matched-unrelated donor (MUD) HCT using either ATG (n=304) or PTCy (n=35) for in vivo T cell manipulation along with a haploidentical PTCy control cohort (n=45). Longitudinal cellular immune reconstitution data were analyzed conventionally and with a data science approach using clustering with dynamic time warping to determine the similarity between time-series of T cell subsets.ResultsConsistent with published studies, no significant differences in clinical outcomes were observed at the cohort level between MUD-ATG and MUD-PTCy. However, cellular reconstitution revealed preferences for distinct T cell subpopulations associating with GVHD protection in each setting. Starting early after HCT, MUD-PTCy patients had higher regulatory T cell levels after HCT (p &lt;0.0001), while MUD-ATG patients presented with higher levels of γδ T- or NKT cells (both p &lt;0.0001). Time-series clustering further dissected the patient population’s heterogeneity revealing distinct immune reconstitution clusters. Importantly, it identified phenotypes that reproducibly associated with impaired clinical outcomes within the same in vivo T cell manipulation platform. Exemplarily, patients with lower activated- and αβ T cell counts had significantly higher NRM (p=0.032) and relapse rates (p =0.01).DiscussionThe improved understanding of the heterogeneity of cellular reconstitution in MUD patients with T cell manipulation both at the cohort and individual level may support clinicians in managing HCT complications

Quality of life in couples living with Huntington’s disease: the role of patients’ and partners’ illness perceptions

Research suggests that chronically ill patients and their partners perceive illness differently, and that these differences have a negative impact on patients’ quality of life (QoL). This study assessed whether illness perceptions of patients with Huntington’s disease (HD) differ from those of their partners, and examined whether spousal illness perceptions are important for the QoL of the couples (n = 51 couples). Partners reported that their HD-patient spouses suffered more symptoms and experienced less control than the patients themselves reported. Illness perceptions of patients and partners correlated significantly with patient QoL. Partners’ beliefs in a long duration of the patients’ illness and less belief in cure, were associated with patient vitality scores. Suggestions for future research emphasize the importance of qualitative research approaches in combination with cognitive-behavioural approaches

Gender differences in patients with dizziness and unsteadiness regarding self-perceived disability, anxiety, depression, and its associations

BACKGROUND: It is known that anxiety and depression influence the level of disability experienced by persons with vertigo, dizziness or unsteadiness. Because higher prevalence rates of disabling dizziness have been found in women and some studies reported a higher level of psychiatric distress in female patients our primary aim was to explore whether women and men with vertigo, dizziness or unsteadiness differ regarding self-perceived disability, anxiety and depression. Secondly we planned to investigate the associations between disabling dizziness and anxiety and depression. METHOD: Patients were recruited from a tertiary centre for vertigo and balance disorders. Participants rated their global disability as mild, moderate or severe. They filled out the Dizziness Handicap Inventory and the two subscales of the Hospital Anxiety Depression Scale (HADS). The HADS was analysed 1) by calculating the median values, 2) by estimating the prevalence rates of abnormal anxiety/depression based on recommended cut-off criteria. Mann-Whitney U-tests, Chi-square statistics and odds ratios (OR) were calculated to compare the observations in both genders. Significance values were adjusted with respect to multiple comparisons. RESULTS: Two-hundred and two patients (124 women) mean age (standard deviation) of 49.7 (13.5) years participated. Both genders did not differ significantly in the mean level of self-perceived disability, anxiety, depression and symptom severity. There was a tendency of a higher prevalence of abnormal anxiety and depression in men (23.7%; 28.9%) compared to women (14.5%; 15.3%). Patients with abnormal depression felt themselves 2.75 (95% CI: 1.31-5.78) times more severely disabled by dizziness and unsteadiness than patients without depression. In men the OR was 8.2 (2.35-28.4). In women chi-square statistic was not significant. The ORs (95% CI) of abnormal anxiety and severe disability were 4.2 (1.9-8.9) in the whole sample, 8.7 (2.5-30.3) in men, and not significant in women. CONCLUSIONS: In men with vertigo, dizziness or unsteadiness emotional distress and its association with self-perceived disability should not be underestimated. Longitudinal surveys with specific pre-defined co-variables of self-perceived disability, anxiety and depression are needed to clarify the influence of gender on disability, anxiety and depression in patients with vertigo, dizziness or unsteadiness