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Abstract Background Tuberous sclerosis complex (TSC) is a rare approximate 1:6000 birth incidence, a genetic disease with a wide variability of physical and neuropsychiatric symptoms. Patients require lifelong care from multiple healthcare specialities, for which International and United Kingdom (UK) TSC consensus recommendations exist. Personalised care delivered by a centralised coordinated team of TSC experts is recommended. There is no such service for the estimated 600 TSC patients in the Republic of Ireland (ROI) and there is a paucity of information regarding the healthcare of this group. Purpose Evaluate the baseline care of patients with TSC attending epilepsy services in the Republic of Ireland (ROI) against UK TSC consensus recommendations. Methods Patients with a diagnosis of TSC attending 12 adult and paediatric epilepsy centres in the ROI were identified. Clinical audits measured the baseline care of a subset of these patients against UK, TSC clinical recommendations. Data was anonymised and analysed at Trinity College Dublin. Results One hundred thirty-five TSC patients attending twelve epilepsy centres were identified. Adults (n = 67) paediatric (n = 68). The care of 83 patients was audited (n = 63 ≥ 18 years) and (n = 20

ABSTRACTBackground: Prior research has shown PTSD treatment leads to reductions in cardiovascular reactivity during trauma recall, but the extent to which such reductions are associated with changes in PTSD symptoms is less clear. Moreover, such relationships have not been investigated in a cognitively focused PTSD treatment.Objective: To examine changes in cardiovascular reactivity to the trauma memory in patients receiving cognitive processing therapy (CPT), CPT with a written trauma account, and a written account only condition. We also examined the association of such changes with symptom improvement.Method: 118 women with PTSD secondary to interpersonal violence completed pre- and post-treatment assessments of PTSD symptoms and cardiovascular reactivity during a script-driven imagery task.Results: Results indicated a significant but modest reduction in cardiovascular reactivity in CPT conditions. Changes in cardiovascular reactivity and reexperiencing symptoms were significantly associated among the whole sample. Among individuals with the greatest reactivity to the trauma memory at pretreatment, associations were also seen with changes in total PTSD, numbing, and trauma-related guilt.Conclusions: Results indicate that previous findings on the effect of PTSD treatment on cardiovascular reactivity during trauma recall extend to cognitively oriented treatment. Baseline cardiovascular reactivity may influence the extent to which reductions in PTSD symptoms and reactivity during trauma recall are related.

Peripheral nerve injury can lead to chronic pain, paralysis, and loss of sensation, severely affecting quality of life. Spinal cord stimulation has been used in the clinic to provide pain relief arising from peripheral nerve injuries, however, its ability to restore function after peripheral nerve injury have not been explored. Neuromodulation of the spinal cord through transcutaneous spinal cord stimulation (tSCS), when paired with activity-based training, has shown promising results towards restoring volitional limb control in people with spinal cord injury. We show, for the first time, the effectiveness of targeted tSCS in restoring strength (407% increase from 1.79 ± 1.24 N to up to 7.3 ± 0.93 N) and significantly increasing hand dexterity in an individual with paralysis due to a peripheral nerve injury (PNI). Furthermore, this is the first study to document a persisting 3-point improvement during clinical assessment of tactile sensation in peripheral injury after receiving 6 weeks of tSCS. Lastly, the motor and sensory gains persisted for several months after stimulation was received, suggesting tSCS may lead to long-lasting benefits, even in PNI. Non-invasive spinal cord stimulation shows tremendous promise as a safe and effective therapeutic approach with broad applications in functional recovery after debilitating injuries.

Long-term recovery of limb function is a significant unmet need in people with paralysis. Neuromodulation of the spinal cord through epidural stimulation, when paired with intense activity-based training, has shown promising results toward restoring volitional limb control in people with spinal cord injury. Non-invasive neuromodulation of the cervical spinal cord using transcutaneous spinal cord stimulation (tSCS) has shown similar improvements in upper-limb motor control rehabilitation. However, the motor and sensory rehabilitative effects of activating specific cervical spinal segments using tSCS have largely remained unexplored. We show in two individuals with motor-complete SCI that targeted stimulation of the cervical spinal cord resulted in up to a 1,136% increase in exerted force, with weekly activity-based training. Furthermore, this is the first study to document up to a 2-point improvement in clinical assessment of tactile sensation in SCI after receiving tSCS. Lastly, participant gains persisted after a one-month period void of stimulation, suggesting that targeted tSCS may lead to persistent recovery of motor and sensory function.

Abstract Melanoma brain metastases (MBM) portend a grim prognosis and can occur in up to 40% of melanoma patients. Genomic characterization of brain metastases has been previously carried out to identify potential mutational drivers. However, to date a comprehensive multi-omics approach has yet to be used to analyze brain metastases. In this case report, we present an unbiased proteogenomics analyses of a patient’s primary skin cancer and three brain metastases from distinct anatomic locations. We performed molecular profiling comprised of a targeted DNA panel and full transcriptome as well as proteomics using mass spectrometry. Phylogeny demonstrated that all MBMs shared a SMARCA4 mutation and deletion of 12q. Proteogenomics identified multiple pathways upregulated in the MBMs compared to the primary tumor. The protein, PIK3CG, was present in many of these pathways and had increased gene expression in metastatic melanoma tissue from the cancer genome atlas data. Proteomics demonstrated PIK3CG levels were significantly increased in all 3 MBMs and this finding was further validated by immunohistochemistry. In summary, this case report highlights the potential role of proteogenomics in identifying pathways involved in metastatic tumor progression. Furthermore, our multi-omics approach can be considered to aid in precision oncology efforts and provide avenues for therapeutic innovation.

ABSTRACT Atypical femur fractures (AFFs) are well‐established serious complication of long‐term bisphosphonate and denosumab therapy in patients with osteopenia or osteoporosis. To elucidate underlying mechanism(s) for the development of AFF, we performed a nested case‐control study to investigate bone tissue nanomechanical properties and prevailing bone microstructure and tissue‐level remodeling status as assessed by bone histomorphometry. We hypothesized that there would be differences in nanomechanical properties between patients with and without AFF and that bone microstructure and remodeling would be related to nanomechanical properties. Thirty‐two full‐thickness transiliac bone biopsies were obtained from age‐ and sex‐matched patients on long‐term bisphosphonate therapy with (n = 16) and without an AFF (n = 16). Standard histomorphometric measurements were made in each sample on three different bone envelopes (cancellous, intracortical, and endosteal). Iliac bone wall thickness was significantly lower on all three bone surfaces in patients with AFF than in those without AFF. Surface‐based bone formation rate was suppressed similarly in both groups in comparison to healthy premenopausal and postmenopausal women, with no significant difference between the two groups. Nanoindentation was used to assess material properties of cortical and cancellous bone separately. Elastic modulus was higher in cortical than in cancellous bone in patients with AFF as well as compared to the elastic modulus of cortical bone from non‐AFF patients. However, the elastic modulus of the cancellous bone was not different between AFF and non‐AFF groups or between cortical and cancellous bone of non‐AFF patients. Resistance to plastic deformation was decreased in cortical bone in both AFF and non‐AFF groups compared to cancellous bone, but to a greater extent in AFF patients. We conclude that long‐term bisphosphonate therapy is associated with prolonged suppression of bone turnover resulting in altered cortical remodeling and tissue nanomechanical properties leading to AFF. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Introduction This study aimed to determine the prevalence of diabetic kidney disease (DKD) and rapid renal function decline and to identify indices associated with this decline among adults attending a diabetes center in Northern Europe.Research design and methods This is a retrospective cohort study of 4606 patients who attended a diabetes center in Ireland between June 2012 and December 2016. Definition/staging of chronic kidney disease used the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 classification based on data from the most recently attended appointment. Relevant longitudinal trends and variabilities were derived from serial records prior to index visit. Rapid renal function decline was defined based on per cent and absolute rates of estimated glomerular filtration rate (eGFR) change. Multiple linear regression was used to explore the relationships between explanatory variables and per cent eGFR change.Results 42.0% (total), 23.4% (type 1 diabetes), 47.9% (type 2 diabetes) and 32.6% (other diabetes) had DKD. Rapid decline based on per cent change was more frequent in type 2 than in type 1 diabetes (32.8% vs 14.0%, p

Impaired kidney function can lead to an increase of β2-microglobulin (β2m) serum levels, which can cause β2m aggregation and amyloid fibril formation. Here the authors combine cryo-EM and magic angle spinning NMR measurements to determine the structure of a β2m fibril and they also present the low resolution model of a β2m fibril with a different morphology.

Objective: To examine the impact of a diabetes renal clinic (DRC) on renal functional and metabolic indices in adults who have diabetes mellitus (DM) and chronic kidney disease (CKD). Patients and Methods: All patients evaluated at a DRC in a single tertiary referral center from January 1, 2008, to December 31, 2012, were identified. Serial renal and metabolic indices from January 1, 2004, to December 31, 2014, were recorded, and trends over time were analyzed by linear mixed-effects models. Results: A total of 200 patients who had DM and CKD were identified and subdivided into 3 categories based on presumptive CKD etiology: 43 (21.5%) with type 1 DM (T1D) only, 127 (63.5%) with type 2 DM (T2D) only, and 30 (15.0%) with DM and an additional CKD etiology. Average annual absolute (mL/min per body surface area per year) and percentage (%/year) changes, respectively, in Chronic Kidney Disease Epidemiology Collaboration estimated glomerular filtration rate before vs after first DRC attendance were: −1.59 vs −3.10 (P=.31) and −1.22 vs −9.39 (P=.06) for T1D; −5.64 vs −3.07 (P=.004) and −10.88 vs −9.94 (P=.70) for T2D; and −6.50 vs +0.91 (P

Colored dissolved organic matter (CDOM), a major component of the dissolved organic carbon (DOC) pool in many lakes, is an important controlling factor in lake ecosystem functioning. Absorption coefficients at 440 nm (a440, m-1), a common measure of CDOM, exhibited strong associations with dissolved iron (Fediss) and DOC in 280 lakes of the Upper Great Lakes States (UGLS: Minnesota, Wisconsin, and Michigan), as has been found in Scandinavia and elsewhere. Linear regressions between the three variables on UGLS lake data typically yielded R2 values of 0.6-0.9, suggesting that some underlying common processes influence organic matter and Fediss. Statistical and experimental evidence, however, supports only a minor role for iron contributions to a440 in UGLS lakes. Although both DOC and Fediss were significant variables in linear and log-log regressions on a440, DOC was the stronger predictor; adding Fediss to the linear a440-DOC model improved the R2 only from 0.90 to 0.93. Furthermore, experimental additions of FeIII to colored lake waters had only small effects on a440 (average increase of 0.242 m-1 per 100 μg/L of added FeIII). For 136 visibly stained waters (with a440 > 3.0 m-1), where allochthonous DOM predominates, DOM accounted for 92.3 ± 5.0% of the measured a440 values, and Fediss accounted for the remainder. In 75% of the lakes, Fediss accounted for < 10% of a440, but contributions of 15-30% were observed for 7 river-influenced lakes. Contributions of Fediss in UGLS lakes to specific UV absorbance at 254 nm (SUVA254) generally were also low. Although Fediss accounted for 5-10% of measured SUVA254 in a few samples, on average, 98.1% of the SUVA254 signal was attributable to DOM and only 1.9% to Fediss. DOC predictions from measured a440 were nearly identical to those from a440 corrected to remove Fediss contributions. Overall, variations in Fediss in most UGLS lakes have very small effects on CDOM optical properties, such as a440 and SUVA254, and negligible effects on the accuracy of DOC estimated from a440, data for which can be obtained at broad regional scales by remote sensing methods.

Very high spatial resolution commercial satellite imagery can inform observation, mapping, and documentation of micro-topographic transitions across large tundra regions. The bridging of fine-scale field studies with pan-Arctic system assessments has until now been constrained by a lack of overlap in spatial resolution and geographical coverage. This likely introduced biases in climate impacts on, and feedback from the Arctic region to the global climate system. The central objective of this exploratory study is to develop an object-based image analysis workflow to automatically extract ice-wedge polygon troughs from very high spatial resolution commercial satellite imagery. We employed a systematic experiment to understand the degree of interoperability of knowledge-based workflows across distinct tundra vegetation units—sedge tundra and tussock tundra—focusing on the same semantic class. In our multi-scale trough modelling workflow, we coupled mathematical morphological filtering with a segmentation process to enhance the quality of image object candidates and classification accuracies. Employment of the master ruleset on sedge tundra reported classification accuracies of correctness of 0.99, completeness of 0.87, and F1 score of 0.92. When the master ruleset was applied to tussock tundra without any adaptations, classification accuracies remained promising while reporting correctness of 0.87, completeness of 0.77, and an F1 score of 0.81. Overall, results suggest that the object-based image analysis-based trough modelling workflow exhibits substantial interoperability across the terrain while producing promising classification accuracies. From an Arctic earth science perspective, the mapped troughs combined with the ArcticDEM can allow hydrological assessments of lateral connectivity of the rapidly changing Arctic tundra landscape, and repeated mapping can allow us to track fine-scale changes across large regions and that has potentially major implications on larger riverine systems.

Across the globe, recent work examining the state of freshwater resources paints an increasingly dire picture of degraded water quality. However, much of this work either focuses on a small subset of large waterbodies or uses in situ water quality datasets that contain biases in when and where sampling occurred. Using these unrepresentative samples limits our understanding of landscape level changes in aquatic systems. In lakes, overall water clarity provides a strong proxy for water quality because it responds to surrounding atmospheric and terrestrial processes. Here, we use satellite remote sensing of over 14 000 lakes to show that lake water clarity in the U.S. has increased by an average of 0.52 cm yr ^−1 since 1984. The largest increases occurred prior to 2000 in densely populated catchments and within smaller waterbodies. This is consistent with observed improvements in water quality in U.S. streams and lakes stemming from sweeping environmental reforms in the 1970s and 1980s that prioritized point-source pollution in largely urban areas. The comprehensive, long-term trends presented here emphasize the need for representative sampling of freshwater resources when examining macroscale trends and are consistent with the idea that extensive U.S. freshwater pollution abatement measures have been effective and enduring, at least for point-source pollution controls.

Deep learning (DL) convolutional neural networks (CNNs) have been rapidly adapted in very high spatial resolution (VHSR) satellite image analysis. DLCNN-based computer visions (CV) applications primarily aim for everyday object detection from standard red, green, blue (RGB) imagery, while earth science remote sensing applications focus on geo object detection and classification from multispectral (MS) imagery. MS imagery includes RGB and narrow spectral channels from near- and/or middle-infrared regions of reflectance spectra. The central objective of this exploratory study is to understand to what degree MS band statistics govern DLCNN model predictions. We scaffold our analysis on a case study that uses Arctic tundra permafrost landform features called ice-wedge polygons (IWPs) as candidate geo objects. We choose Mask RCNN as the DLCNN architecture to detect IWPs from eight-band Worldview-02 VHSR satellite imagery. A systematic experiment was designed to understand the impact on choosing the optimal three-band combination in model prediction. We tasked five cohorts of three-band combinations coupled with statistical measures to gauge the spectral variability of input MS bands. The candidate scenes produced high model detection accuracies for the F1 score, ranging between 0.89 to 0.95, for two different band combinations (coastal blue, blue, green (1,2,3) and green, yellow, red (3,4,5)). The mapping workflow discerned the IWPs by exhibiting low random and systematic error in the order of 0.17–0.19 and 0.20–0.21, respectively, for band combinations (1,2,3). Results suggest that the prediction accuracy of the Mask-RCNN model is significantly influenced by the input MS bands. Overall, our findings accentuate the importance of considering the image statistics of input MS bands and careful selection of optimal bands for DLCNN predictions when DLCNN architectures are restricted to three spectral channels.