Modifications in fMRI Representation of Mental Rotation Following a 6 Week Graded Motor Imagery Training in Chronic CRPS Patients

Complex regional pain syndrome (CRPS) is a neuropathic pain condition that is difficult to treat. For behavioral interventions, graded motor imagery (GMI) showed relevant effects, but underlying neural substrates in patient groups have not been investigated yet. A previous study investigating differences in the representation of a left/right hand judgment task demonstrated less recruitment of subcortical structures, such as the putamen, in CRPS patients than in healthy controls. In healthy volunteers, the putamen activity increased after a hand judgment task training. In order to test for longitudinal effects of GMI training, we investigated 20 CRPS patients in a wait-list crossover design with 3 evaluation time points. Patients underwent a 6 week GMI treatment and a 6 week waiting period in a randomized group assignment and treatment groups were evaluated by a blinded rater. When compared to healthy matched controls at baseline, CRPS patients showed less functional activation in areas processing visual input, left sensorimotor cortex, and right putamen. Only GMI treatment, but not the waiting period showed an effect on movement pain and hand judgment task performance. Regression analyses revealed positive associations of movement pain with left anterior insula activation at baseline. Right intraparietal sulcus activation change during GMI was associated with a gain in performance of the hand judgment task. The design used here is reliable for investigating the functional representation of the hand judgment task in an intervention study.PerspectiveTwenty chronic CRPS patients underwent a 6 week GMI intervention in a randomized wait-list crossover design. functional MRI was tested pre and post for the hand lateralization task which improved over GMI but not over WAITING. Performance gain was positively related to right parietal functional MRI activation.     

Next-generation sequencing in X-linked intellectual disability

X-linked intellectual disability (XLID) is a genetically heterogeneous disorder with more than 100 genes known to date. Most genes are responsible for a small proportion of patients only, which has hitherto hampered the systematic screening of large patient cohorts. We performed targeted enrichment and next-generation sequencing of 107 XLID genes in a cohort of 150 male patients. Hundred patients had sporadic intellectual disability, and 50 patients had a family history suggestive of XLID. We also analysed a sporadic female patient with severe ID and epilepsy because she had strongly skewed X-inactivation. Target enrichment and high parallel sequencing allowed a diagnostic coverage of >10 reads for ~96% of all coding bases of the XLID genes at a mean coverage of 124 reads. We found 18 pathogenic variants in 13 XLID genes (AP1S2, ATRX, CUL4B, DLG3, IQSEC2, KDM5C, MED12, OPHN1, SLC9A6, SMC1A, UBE2A, UPF3B and ZDHHC9) among the 150 male patients. Thirteen pathogenic variants were present in the group of 50 familial patients (26%), and 5 pathogenic variants among the 100 sporadic patients (5%). Systematic gene dosage analysis for low coverage exons detected one pathogenic hemizygous deletion. An IQSEC2 nonsense variant was detected in the female ID patient, providing further evidence for a role of this gene in encephalopathy in females. Skewed X-inactivation was more frequently observed in mothers with pathogenic variants compared with those without known X-linked defects. The mutation rate in the cohort of sporadic patients corroborates previous estimates of 5–10% for X-chromosomal defects in male ID patients.     

Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction

Aerosol–cloud interaction (ACI) is complex and difficult to be well represented in current climate models. Progress on understanding ACI processes, such as the influence of aerosols on water cloud droplet formation, is hampered by inadequate observational capability. Hitherto, high-resolution and simultaneous observations of diurnal aerosol loading and cloud microphysical properties are challenging for current remote-sensing techniques. To overcome this conundrum, we introduce the dual-field-of-view (FOV) high-spectral-resolution lidar (HSRL) for simultaneously profiling aerosol and water cloud properties, especially water cloud microphysical properties. Continuous observations of aerosols and clouds using this instrument, verified by the Monte Carlo simulation and coincident observations of other techniques, were conducted to investigate the interactions between aerosol loading and water cloud microphysical properties. A case study over Beijing highlights the scientific potential of dual-FOV HSRL to become a significant contributor to the ACI investigations. The observed water cloud profiles identify that due to air entrainment its vertical structure is not perfectly adiabatic, as assumed by many current retrieval methods. Our ACI analysis shows increased aerosol loading led to increased droplet number concentration and decreased droplet effective radius—consistent with expectations—but had no discernible increase on liquid water path. This finding supports the hypothesis that aerosol-induced cloud water increase caused by suppressed rain formation can be canceled out by enhanced evaporation. Thus, these observations obtained from the dual-FOV HSRL constitute substantial and significant additions to understanding ACI process. This technique is expected to represent a significant step forward in characterizing ACI.

Aerosol–cloud interaction (ACI) is a crucial aspect of atmospheric research and one of the primary sources of uncertainties in climate predictions (1–3). To assess the credibility of climate projections, it is imperative to improve our understanding of how aerosols interact with clouds (4–6). It has been well known that aerosols can serve as cloud condensation nuclei (CCN) to form cloud droplets, which can further influence the initiation of precipitation (7). However, quantifying the impact of natural and anthropogenic aerosols on the growth and the evolution of water clouds is still challenging (8, 9). The short lifetime, high temporal variability, and complex vertical structure of water cloud layers lead to a major difficulty for ACI studies (3, 10, 11). Despite the advances in the characterization of ACI by ground-based measurements (12–21), satellite retrieved products (22–25), and airborne in situ measurements (26–28), uncertainties remain in the effects of the aerosols on the water cloud properties. The reason for this gap in our knowledge is closely linked to the inadequate observations of the water cloud microphysical properties under various aerosol conditions (3). Current satellites can estimate cloud properties but not the typical aerosol nucleation region beneath clouds (22–25). Moreover, they also bring challenges for ACI studies that the typical revisit time of satellite-based sensors is much longer than the temporal scales of cloud variability (29, 30). Quintessential ground-based remote-sensing techniques for retrieving cloud properties, such as the cloud radar and the microwave radiometer, cannot provide simultaneous aerosol observations for ACI studies. Therefore, ground-based measurements commonly combine those with other remote-sensing or in situ aircraft instruments for characterizing aerosol loading beneath clouds (12–20). However, given the high variability of clouds, differences in perspective or mismatched sampling in space and time would raise uncertainty and bias in the characterization of ACI (15).Lidar, a powerful tool for profiling optical properties of aerosols and clouds, has been widely used in atmospheric studies (31–33). Yet, further progress with lidar-based techniques for ACI studies is hampered by limited observations of the water cloud microphysical properties, mainly due to the difficulties of quantifying the multiple scattering within water clouds (34). The multiple scattering has a significant impact on the water cloud observations of the extinction as well as the depolarization ratio, which is related to the receiver field of view (FOV). In brief, a retrieval of water cloud microphysical properties for lidar-based techniques relies on utilizing different receiver FOVs to provide the necessary observations for characterizing the multiple-scattering effect caused by the water droplets (34, 35). The first multiple-FOV lidars were aimed at investigating the multiple-scattering effect and measured Mie scattering by water droplets (36). However, a complicated behavior of the Mie phase function makes the quantifying of the multiple scattering become an arduous task. It naturally leads to the use of Raman scattering of atmospheric nitrogen, which has an isotropic phase function practically in the backward direction, to allow developing a feasible algorithm for the retrieval of water cloud microphysical properties (35). Moreover, the dual-FOV Raman lidar technique for profiling cloud properties has been experimentally demonstrated (37). With this technique in conjunction with an incoherent Doppler lidar, the ACI findings have been obtained with an ACI index versus vertical air motion (21, 38). However, nitrogen Raman signals are so weak that the observations are usually restricted to nighttime hours, and the signal has to be averaged over tens of minutes to deliver reliable lidar products, while the typical temporal scale of cloud variability is much shorter than that (29). Recently, a dual-FOV polarization lidar technique was reported, which continued and further developed the concept of the dual-FOV Mie lidar (39). However, to assess ACI this method requires a priori assumptions about the lidar ratio and subadiabatic cloud conditions. The impact of the a priori assumptions on the aerosol and cloud retrievals has been widely discussed (10, 40, 41). In general, all existing multiple-FOV lidar-based techniques have their advantages and also limitations.To overcome this conundrum, a dual-FOV high-spectral-resolution lidar (HSRL) technique for profiling aerosol and cloud properties simultaneously is introduced here. It provides lateral observations of aerosols and clouds with high vertical and temporal resolutions during daytime and nighttime. Neither assumptions on thermodynamic conditions nor lidar ratio are required. This work benefited from the range-resolved observations of water clouds with high resolution, revealing that the observed profiles of low-level water cloud microphysical properties are not perfectly adiabatic as assumed by many current retrievals (42–46). Furthermore, the ACI analysis supports the hypothesis that aerosol-induced water decrease by enhanced evaporation can cancel out the increase caused by suppressed rain formation (6, 47), while most current global general circulation models (GCMs) suggest that increased aerosol loading typically causes increased cloud water content (19, 48). Thus, these observations obtained from the dual-FOV HSRL can constitute a substantial and significant addition to our understanding of ACI studies. We believe that this versatile system will not only benefit the quality monitoring of aerosol and cloud properties but also serve as a powerful tool for ACI studies.     

Association between Lp-PLA2 and coronary artery disease: focus on its relationship with lipoproteins and markers of inflammation and hemostasis

Lipoprotein-associated phospholipase A2 (Lp-PLA2) generates pro-inflammatory molecules from oxidized LDL. We examined the association between Lp-PLA2 plasma concentrations and risk of stable coronary artery disease (CAD) in a large case-control study and further assessed the relationship between Lp-PLA2 and various lipid, inflammatory and hemostatic parameters. Lp-PLA2 concentrations were measured in 312 patients with CAD and in 479 age- and gender-matched blood donors. Various sensitive inflammatory and hemostatic markers and a complete lipoprotein profile were obtained. Lp-PLA2 concentrations were significantly higher in cases than in controls (296.1 ng/mL versus 266.0 ng/mL, p<0.0001). In multivariable logistic regression, the age- and gender-adjusted OR for the presence of CAD was 1.61 (95% CI, 1.07-2.44) if the top quartile of the Lp-PLA2 distribution was compared to the bottom quartile. Adjustment for traditional cardiovascular risk factors and statin use resulted in an OR of 2.04 (95% CI, 1.19-3.48). After additional controlling for vWF, the OR was slightly attenuated but still remained statistically significant (OR 1.91; 95% CI, 1.12-3.28). Thus, elevated Lp-PLA2 concentrations were associated with the presence of stable CAD, independent of various biochemical markers. Our results support the hypothesis that Lp-PLA2 may be a novel, independent risk marker for CAD.     

Expression mapping of tetracycline-responsive prion protein promoter: digital atlasing for generating cell-specific disease models

We present a digital atlas system that allows mapping of molecular expression patterns at cellular resolution through large series of histological sections. Using this system, we have mapped the distribution of a distinct marker, encoded by the LacZ reporter gene driven by the tetracycline-responsive prion protein promoter in double transgenic mice. The purpose is to evaluate the suitability of this promoter mouse line for targeting genes of interest to specific brain regions, essential for construction of inducible transgenic disease models. Following processing to visualize the promoter expression, sections were counterstained to simultaneously display cytoarchitectonics. High-resolution mosaic images covering entire coronal sections were collected through the mouse brain at intervals of 200 microm. A web-based application provides access to a customized virtual microscopy tool for viewing and navigation within and across the section images. For each section image, the nearest section in a standard atlas is defined, and annotations of key structures and regions inserted. Putative categorization of labeled cells was performed with use of distribution patterns, followed by cell size and shape, as parameters that were compared to legacy data. Among the ensuing results were expression of this promoter in putative glial cells in the cerebellum (and not in Purkinje cells), in putative glial cells in the substantia nigra, in pallidal glial cells or interneurons, and in distinct cell layers and regions of the hippocampus. The study serves as a precursor for a database resource allowing evaluation of the suitability of different promoter mouse lines for generating disease models.     

Mixed-signal template-based reduction scheme for stimulus artifact removal in electrical stimulation

Simultaneous electrical stimulation and recording are used to gain insights into the function of neuronal circuitry. However, artifacts produced by the electrical stimulation pulses prevent the recording of neural responses during, and a short period after, the stimulation duration. In this work, we describe a mixed-signal recording topology with template subtraction for removing the artifact during the stimulation pulse. Emulated artifacts generated from a lumped electrical circuit model and experimental artifacts in cardiac cell cultures are used to evaluate the topology. The simulations show that delays between the emulated artifact and its estimated compensation template represent the largest error source of the analog template subtraction. The quantization error appears like random noise and determines the threshold level for the action potential detection. Simulations show that removal of the artifacts is possible, allowing the detection of action potentials during the stimulation pulsing period, even for high-amplitude saturating artifacts. Measurement results with artifacts elicited in cardiac cell cultures show feasible applications of this topology. The proposed topology therefore promisingly opens up a previously unavailable detection window for improving the analysis of the neuronal activity.