Modelling the power threshold and optimum thermal deformation of indirectly liquid-nitrogen cryo-cooled Si monochromators

Maximizing the performance of crystal monochromators is a key aspect in the design of beamline optics for diffraction-limited synchrotron sources. Temperature and deformation of cryo-cooled crystals, illuminated by high-power beams of X-rays, can be estimated with a purely analytical model. The analysis is based on the thermal properties of cryo-cooled silicon crystals and the cooling geometry. Deformation amplitudes can be obtained, quickly and reliably. In this article the concept of threshold power conditions is introduced and defined analytically. The contribution of parameters such as liquid-nitrogen cooling efficiency, thermal contact conductance and interface contact area of the crystal with the cooling base is evaluated. The optimal crystal illumination and the base temperature are inferred, which help minimize the optics deformation. The model has been examined using finite-element analysis studies performed for several beamlines of the Diamond-II upgrade.

Abrupt and acclimation responses to changing temperature elicit divergent physiological effects in the diatom Phaeodactylum tricornutum

Growth rates and other biomass traits of phytoplankton are strongly affected by temperature. We hypothesized that resulting phenotypes originate from deviating temperature sensitivities of underlying physiological processes. We used membrane-inlet mass spectrometry to assess photosynthetic and respiratory O₂ and CO₂ fluxes in response to abrupt temperature changes as well as after acclimation periods in the diatom Phaeodactylum tricornutum. Abrupt temperature changes caused immediate over- or undershoots in most physiological processes, that is, photosynthetic oxygen release ( PS O 2 $$ {\mathrm{PS}}_{{\mathrm{O}}_2} $$ ), photosynthetic carbon uptake ( PS CO 2 $$ {\mathrm{PS}}_{{\mathrm{CO}}_2} $$ ), and respiratory oxygen release ( R O 2 $$ {\mathrm{R}}_{{\mathrm{O}}_2} $$ ). Over acclimation timescales, cells were, however, able to re-adjust their physiology and revert to phenotypic 'sweet spots'. Respiratory CO₂ release ( R CO 2 $$ {\mathrm{R}}_{{\mathrm{CO}}_2} $$ ) was generally inhibited under high temperature and stimulated under low-temperature settings, on abrupt as well as acclimation timescales. Such behavior may help mitochondria to stabilize plastidial ATP : NADPH ratios and thus maximize photosynthetic carbon assimilation.

Programming of subthalamic nucleus deep brain stimulation for Parkinson's disease with sweet spot-guided parameter suggestions

Deep Brain Stimulation (DBS) is an effective treatment for advanced Parkinson's disease. However, identifying stimulation parameters, such as contact and current amplitudes, is time-consuming based on trial and error. Directional leads add more stimulation options and render this process more challenging with a higher workload for neurologists and more discomfort for patients. In this study, a sweet spot-guided algorithm was developed that automatically suggested stimulation parameters. These suggestions were retrospectively compared to clinical monopolar reviews. A cohort of 24 Parkinson's disease patients underwent bilateral DBS implantation in the subthalamic nucleus at our center. First, the DBS' leads were reconstructed with the open-source toolbox Lead-DBS. Second, a sweet spot for rigidity reduction was set as the desired stimulation target for programming. This sweet spot and estimations of the volume of tissue activated were used to suggest (i) the best lead level, (ii) the best contact, and (iii) the effect thresholds for full therapeutic effect for each contact. To assess these sweet spot-guided suggestions, the clinical monopolar reviews were considered as ground truth. In addition, the sweet spot-guided suggestions for best lead level and best contact were compared against reconstruction-guided suggestions, which considered the lead location with respect to the subthalamic nucleus. Finally, a graphical user interface was developed as an add-on to Lead-DBS and is publicly available. With the interface, suggestions for all contacts of a lead can be generated in a few seconds. The accuracy for suggesting the best out of four lead levels was 56%. These sweet spot-guided suggestions were not significantly better than reconstruction-guided suggestions (p = 0.3). The accuracy for suggesting the best out of eight contacts was 41%. These sweet spot-guided suggestions were significantly better than reconstruction-guided suggestions (p < 0.001). The sweet spot-guided suggestions of each contact's effect threshold had a mean error of 1.2 mA. On an individual lead level, the suggestions can vary more with mean errors ranging from 0.3 to 4.8 mA. Further analysis is warranted to improve the sweet spot-guided suggestions and to account for more symptoms and stimulation-induced side effects.

Impact Position Estimation for Baseball Batting with a Force-Irrelevant Vibration Feature

In this work we propose a novel method for impact position estimation during baseball batting, which is independent of impact intensity, i.e., force-irrelevant. In our experiments, we mount a piezoelectric vibration sensor on the knob of a wooden bat to record: (1) 3600 vibration signals (waveforms) from ball–bat impacts in the static experiment—30 impacts from each of 40 positions (distributed 1–40 cm from the end of the barrel) and 3 intensities (drop heights at 75, 100, and 125 cm, resp.), and (2) 45 vibration signals from actual battings by three baseball players in the dynamic experiment. The results show that the peak amplitude of the signal in the time domain, and the peaks of the first, second, and third eigenfrequencies (EFs) of the bat all increase with the impact intensity. However, the ratios of peaks at these three EFs (1st/2nd, 2nd/3rd, and 1st/3rd) hardly change with the impact intensity, and the observation is consistent for both the static and dynamic experiments across all impact positions. In conclusion, we have observed that the ratios of peaks at the first three EFs are a force-irrelevant feature, which can be used to estimate the impact position in baseball batting.

How Should we Use Multicolumn Spinal Cord Stimulation to Optimize Back Pain Spatial Neural Targeting? A Prospective, Multicenter, Randomized, Double-Blind, Controlled Trial (ESTIMET Study)

BACKGROUND

Recent studies have highlighted multicolumn spinal cord stimulation (SCS) efficacy, hypothesizing that optimized spatial neural targeting provided by new-generation SCS lead design or its multicolumn programming abilities could represent an opportunity to better address chronic back pain (BP).

OBJECTIVE

To compare multicolumn vs. monocolumn programming on clinical outcomes of refractory postoperative chronic BP patients implanted with SCS using multicolumn surgical lead.

MATERIALS AND METHODS

Twelve centers included 115 patients in a multicenter, randomized, double-blind, controlled trial. After randomization, leads were programmed using only one or several columns. The primary outcome was change in BP visual analogic scale (VAS) at six months. All patients were then programmed using the full potential of the lead up until 12-months follow-up.

RESULTS

At six months, there was no significant difference in clinical outcomes whether the SCS was programmed using a mono or a multicolumn program. At 12 months, in all patients having been receiving multicolumn SCS for at least six months (n = 97), VAS decreases were significant for global pain (45.1%), leg pain (55.8%), and BP (41.5%) compared with baseline (p < 0.0001).

CONCLUSION

The ESTIMET study confirms the significant benefit experienced on chronic BP by patients implanted with multicolumn SCS, independently from multicolumn lead programming. These good clinical outcomes might result from the specific architecture of the multicolumn lead, giving the opportunity to select initially the best column on a multicolumn grid and to optimize neural targeting with low-energy requirements. However, involving more columns than one does not appear necessary, once initial spatial targeting of the "sweet spot" has been achieved. Our findings suggest that this spatial concept could also be transposed to cylindrical leads, which have drastically improved their capability to shape the electrical field, and might be combined with temporal resolution using SCS new modalities.

Connectivity profile of thalamic deep brain stimulation to effectively treat essential tremor

Essential tremor is the most prevalent movement disorder and is often refractory to medical treatment. Deep brain stimulation offers a therapeutic approach that can efficiently control tremor symptoms. Several deep brain stimulation targets (ventral intermediate nucleus, zona incerta, posterior subthalamic area) have been discussed for tremor treatment. Effective deep brain stimulation therapy for tremor critically involves optimal targeting to modulate the tremor network. This could potentially become more robust and precise by using state-of-the-art brain connectivity measurements. In the current study, we used two normative brain connectomes (structural and functional) to show the pattern of effective deep brain stimulation electrode connectivity in 36 patients with essential tremor. Our structural and functional connectivity models were significantly predictive of postoperative tremor improvement in out-of-sample data (P < 0.001 for both structural and functional leave-one-out cross-validation). Additionally, we segregated the somatotopic brain network based on head and hand tremor scores. These resulted in segregations that mapped onto the well-known somatotopic maps of both motor cortex and cerebellum. Crucially, this shows that slightly distinct networks need to be modulated to ameliorate head versus hand tremor and that those networks could be identified based on somatotopic zones in motor cortex and cerebellum. Finally, we propose a multi-modal connectomic deep brain stimulation sweet spot that may serve as a reference to enhance clinical care, in the future. This spot resided in the posterior subthalamic area, encroaching on the inferior borders of ventral intermediate nucleus and sensory thalamus. Our results underscore the importance of integrating brain connectivity in optimizing deep brain stimulation targeting for essential tremor.

Probabilistic mapping of the antidystonic effect of pallidal neurostimulation: a multicentre imaging study

Deep brain stimulation of the internal globus pallidus is a highly effective and established therapy for primary generalized and cervical dystonia, but therapeutic success is compromised by a non-responder rate of up to 25%, even in carefully-selected groups. Variability in electrode placement and inappropriate stimulation settings may account for a large proportion of this outcome variability. Here, we present probabilistic mapping data on a large cohort of patients collected from several European centres to resolve the optimal stimulation volume within the pallidal region. A total of 105 dystonia patients with pallidal deep brain stimulation were enrolled and 87 datasets (43 with cervical dystonia and 44 with generalized dystonia) were included into the subsequent 'normative brain' analysis. The average improvement of dystonia motor score was 50.5 ± 30.9% in cervical and 58.2 ± 48.8% in generalized dystonia, while 19.5% of patients did not respond to treatment (<25% benefit). We defined probabilistic maps of anti-dystonic effects by aggregating individual electrode locations and volumes of tissue activated (VTA) in normative atlas space and ranking voxel-wise for outcome distribution. We found a significant relation between motor outcome and the stimulation volume, but not the electrode location per se. The highest probability of stimulation induced motor benefit was found in a small volume covering the ventroposterior globus pallidus internus and adjacent subpallidal white matter. We then used the aggregated VTA-based outcome maps to rate patient individual VTAs and trained a linear regression model to predict individual outcomes. The prediction model showed robustness between the predicted and observed clinical improvement, with an r2 of 0.294 (P < 0.0001). The predictions deviated on average by 16.9 ± 11.6 % from observed dystonia improvements. For example, if a patient improved by 65%, the model would predict an improvement between 49% and 81%. Results were validated in an independent cohort of 10 dystonia patients, where prediction and observed benefit had a correlation of r2 = 0.52 (P = 0.02) and a mean prediction error of 10.3% (±8.9). These results emphasize the potential of probabilistic outcome brain mapping in refining the optimal therapeutic volume for pallidal neurostimulation and advancing computer-assisted planning and programming of deep brain stimulation.

Discovery of a Sweet Spot on the Foot with a Smart Wearable Soccer Boot Sensor That Maximizes the Chances of Scoring a Curved Kick in Soccer

This paper provides the evidence of a sweet spot on the boot/foot as well as the method for detecting it with a wearable pressure sensitive device. This study confirmed the hypothesized existence of sweet and dead spots on a soccer boot or foot when kicking a ball. For a stationary curved kick, kicking the ball at the sweet spot maximized the probability of scoring a goal (58-86%), whereas having the impact point at the dead zone minimized the probability (11-22%). The sweet spot was found based on hypothesized favorable parameter ranges (center of pressure in x/y-directions and/or peak impact force) and the dead zone based on hypothesized unfavorable parameter ranges. The sweet spot was rather concentrated, independent of which parameter combination was used (two- or three-parameter combination), whereas the dead zone, located 21 mm from the sweet spot, was more widespread.

Correlation between Sweet Spots of Glycopeptides and Polymorphism of the Matrix Crystal in MALDI Samples

A standard dried-droplet preparation using 2,5-dihydroxybenzoic acid (2,5-DHBA) as the matrix results in a large variation in signal intensity and poor shot-to-shot reproducibility in matrix-assisted laser desorption/ionization (MALDI). We expected that the differences can be attributed to the nature of the crystal structures in the region of the "sweet spot" within the MALDI samples. 2,5-DHBA crystals with and without analytes on a target plate obtained by means of a dried-droplet preparation contain two polymorphs, which can be distinguished by Raman spectra. In comparing the Raman image with the MS image, a clear correlation between the signal distribution of glycopeptides and hydrophilic peptides and the specific crystal form of 2,5-DHBA could be made. The ionization of hydrophobic peptides appears to proceed in both types of polymorphic crystals. In addition, the derivatization of glycopeptides with a pyrene group enabled us to detect glycopeptides regardless the crystal form. As the result, the number of sweet spots increased and MS spectra with a high signal intensity were obtained. The results suggest that the introduction of a hydrophobic/aromatic moiety to glycopeptides results in a more successful MALDI analysis due to the effective incorporation of the analyte into matrix crystals.