Predicting RNA sequence-structure likelihood via structure-aware deep learning.

BACKGROUND: The active functionalities of RNA are recognized to be heavily dependent on the structure and sequence. Therefore, a model that can accurately evaluate a design by giving RNA sequence-structure pairs would be a valuable tool for many researchers. Machine learning methods have been explored to develop such tools, showing promising results. However, two key issues remain. Firstly, the performance of machine learning models is affected by the features used to characterize RNA. Currently, there is no consensus on which features are the most effective for characterizing RNA sequence-structure pairs. Secondly, most existing machine learning methods extract features describing entire RNA molecule. We argue that it is essential to define additional features that characterize nucleotides and specific sections of RNA structure to enhance the overall efficacy of the RNA design process. RESULTS: We develop two deep learning models for evaluating RNA sequence-secondary structure pairs. The first model, NU-ResNet, uses a convolutional neural network architecture that solves the aforementioned problems by explicitly encoding RNA sequence-structure information into a 3D matrix. Building upon NU-ResNet, our second model, NUMO-ResNet, incorporates additional information derived from the characterizations of RNA, specifically the 2D folding motifs. In this work, we introduce an automated method to extract these motifs based on fundamental secondary structure descriptions. We evaluate the performance of both models on an independent testing dataset. Our proposed models outperform the models from literatures in this independent testing dataset. To assess the robustness of our models, we conduct 10-fold cross validation. To evaluate the generalization ability of NU-ResNet and NUMO-ResNet across different RNA families, we train and test our proposed models in different RNA families. Our proposed models show superior performance compared to the models from literatures when being tested across different independent RNA families. CONCLUSIONS: In this study, we propose two deep learning models, NU-ResNet and NUMO-ResNet, to evaluate RNA sequence-secondary structure pairs. These two models expand the field of data-driven approaches for learning RNA. Furthermore, these two models provide the new method to encode RNA sequence-secondary structure pairs.

mNG-tagged fusion proteins and nanobodies to visualize tropomyosins in yeast and mammalian cells.

Tropomyosins are structurally conserved α-helical coiled-coil proteins that bind along the length of filamentous actin (F-actin) in fungi and animals. Tropomyosins play essential roles in the stability of actin filaments and in regulating myosin II contractility. Despite the crucial role of tropomyosin in actin cytoskeletal regulation, in vivo investigations of tropomyosin are limited, mainly due to the suboptimal live-cell imaging tools currently available. Here, we report on an mNeonGreen (mNG)-tagged tropomyosin, with native promoter and linker length configuration, that clearly reports tropomyosin dynamics in Schizosaccharomyces pombe (Cdc8), Schizosaccharomyces japonicus (Cdc8) and Saccharomyces cerevisiae (Tpm1 and Tpm2). We also describe a fluorescent probe to visualize mammalian tropomyosin (TPM2 isoform). Finally, we generated a camelid nanobody against S. pombe Cdc8, which mimics the localization of mNG-Cdc8 in vivo. Using these tools, we report the presence of tropomyosin in previously unappreciated patch-like structures in fission and budding yeasts, show flow of tropomyosin (F-actin) cables to the cytokinetic actomyosin ring and identify rearrangements of the actin cytoskeleton during mating. These powerful tools and strategies will aid better analyses of tropomyosin and F-actin cables in vivo.

Higher precision, first tier newborn screening for metachromatic leukodystrophy using 16:1-OH-sulfatide.

Newborn screening (NBS) for metachromatic leukodystrophy (MLD) is based on first-tier measurement of sulfatides in dried blood spots (DBS) followed by second-tier measurement of arylsulfatase A in the same DBS. This approach is very precise with 0-1 false positives per ∼30,000 newborns tested. Recent data reported here shows that the sulfatide molecular species with an α-hydroxyl, 16­carbon, mono-unsaturated fatty acyl group (16:1-OH-sulfatide) is superior to the original biomarker 16:0-sulfatide in reducing the number of first-tier false positives. This result is consistent across 4 MLD NBS centers. By measuring 16:1-OH-sulfatide alone or together with 16:0-sulfatide, the estimated false positive rate is 0.048% and is reduced essentially to zero with second-tier arylsulfatase A activity assay. The false negative rate is predicted to be extremely low based on the demonstration that 40 out of 40 newborn DBS from clinically-confirmed MLD patients are detected with these methods. The work shows that NBS for MLD is extremely precise and ready for deployment. Furthermore, it can be multiplexed with several other inborn errors of metabolism already tested in NBS centers worldwide.

Improving newborn screening test performance for metachromatic leukodystrophy: Recommendation from a pre-pilot study that identified a late-infantile case for treatment.

Metachromatic leukodystrophy (MLD) is a devastating rare neurodegenerative disease. Typically, loss of motor and cognitive skills precedes early death. The disease is characterised by deficient lysosomal arylsulphatase A (ARSA) activity and an accumulation of undegraded sulphatide due to pathogenic variants in the ARSA gene. Atidarsagene autotemcel (arsa-cel), an ex vivo haematopoietic stem cell gene therapy was approved for use in the UK in 2021 to treat early-onset forms of pre- or early-symptomatic MLD. Optimal outcomes require early diagnosis, but in the absence of family history this is difficult to achieve without newborn screening (NBS). A pre-pilot MLD NBS study was conducted as a feasibility study in Manchester UK using a two-tiered screening test algorithm. Pre-established cutoff values (COV) for the first-tier C16:0 sulphatide (C16:0-S) and the second-tier ARSA tests were evaluated. Before the pre-pilot study, initial test validation using non­neonatal diagnostic bloodspots demonstrated ARSA pseudodeficiency status was associated with normal C16:0-S results for age (n = 43) and hence not expected to cause false positive results in this first-tier test. Instability of ARSA in bloodspot required transfer of NBS bloodspots from ambient temperature to -20°C storage within 7-8 days after heel prick, the earliest possible in this UK pre-pilot study. Eleven of 3687 de-identified NBS samples in the pre-pilot were positive for C16:0-S based on the pre-established COV of ≥170 nmol/l or ≥ 1.8 multiples of median (MoM). All 11 samples were subsequently tested negative determined by the ARSA COV of <20% mean of negative controls. However, two of 20 NBS samples from MLD patients would be missed by this C16:0-S COV. A further suspected false negative case that displayed 4% mean ARSA activity by single ARSA analysis for the initial test validation was confirmed by genotyping of this NBS bloodspot, a severe late infantile MLD phenotype was predicted. This led to urgent assessment of this child by authority approval and timely commencement of arsa-cel gene therapy at 11 months old. Secondary C16:0-S analysis of this NBS bloodspot was 150 nmol/l or 1.67 MoM. This was the lowest result reported thus far, a new COV of 1.65 MoM is recommended for future pilot studies. Furthermore, preliminary data of this study showed C16:1-OH sulphatide is more specific for MLD than C16:0-S. In conclusion, this pre-pilot study adds to the international evidence that recommends newborn screening for MLD, making it possible for patients to benefit fully from treatment through early diagnosis.

Multisite thalamic recordings to characterize seizure propagation in the human brain.

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in a subset of patients with refractory focal epilepsy. One important uncertainty is to what extent thalamic subregions other than the ANT could be recruited more prominently in the propagation of focal onset seizures. We designed the current study to simultaneously monitor the engagement of the ANT, mediodorsal (MD) and pulvinar (PUL) nuclei during seizures in patients who could be candidates for thalamic neuromodulation. We studied 11 patients with clinical manifestations of presumed temporal lobe epilepsy (TLE) undergoing invasive stereo-encephalography (sEEG) monitoring to confirm the source of their seizures. We extended cortical electrodes to reach the ANT, MD and PUL nuclei of the thalamus. More than one thalamic subdivision was simultaneously interrogated in nine patients. We recorded seizures with implanted electrodes across various regions of the brain and documented seizure onset zones (SOZ) in each recorded seizure. We visually identified the first thalamic subregion to be involved in seizure propagation. Additionally, in eight patients, we applied repeated single pulse electrical stimulation in each SOZ and recorded the time and prominence of evoked responses across the implanted thalamic regions. Our approach for multisite thalamic sampling was safe and caused no adverse events. Intracranial EEG recordings confirmed SOZ in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites, highlighting the importance of invasive monitoring for accurate localization of SOZs. In all patients, seizures with the same propagation network and originating from the same SOZ involved the same thalamic subregion, with a stereotyped thalamic EEG signature. Qualitative visual reviews of ictal EEGs were largely consistent with the quantitative analysis of the corticothalamic evoked potentials, and both documented that thalamic nuclei other than ANT could have the earliest participation in seizure propagation. Specifically, pulvinar nuclei were involved earlier and more prominently than ANT in more than half of the patients. However, which specific thalamic subregion first demonstrated ictal activity could not be reliably predicted based on clinical semiology or lobar localization of SOZs. Our findings document the feasibility and safety of bilateral multisite sampling from the human thalamus. This may allow more personalized thalamic targets to be identified for neuromodulation. Future studies are needed to determine if a personalized thalamic neuromodulation leads to greater improvements in clinical outcome.

E-BDL: Enhanced Band-Dependent Learning Framework for Augmented Radar Sensing.

Radar sensors, leveraging the Doppler effect, enable the nonintrusive capture of kinetic and physiological motions while preserving privacy. Deep learning (DL) facilitates radar sensing for healthcare applications such as gait recognition and vital-sign measurement. However, band-dependent patterns, indicating variations in patterns and power scales associated with frequencies in time-frequency representation (TFR), challenge radar sensing applications using DL. Frequency-dependent characteristics and features with lower power scales may be overlooked during representation learning. This paper proposes an Enhanced Band-Dependent Learning framework (E-BDL) comprising an adaptive sub-band filtering module, a representation learning module, and a sub-view contrastive module to fully detect band-dependent features in sub-frequency bands and leverage them for classification. Experimental validation is conducted on two radar datasets, including gait abnormality recognition for Alzheimer's disease (AD) and AD-related dementia (ADRD) risk evaluation and vital-sign monitoring for hemodynamics scenario classification. For hemodynamics scenario classification, E-BDL-ResNet achieves competitive performance in overall accuracy and class-wise evaluations compared to recent methods. For ADRD risk evaluation, the results demonstrate E-BDL-ResNet's superior performance across all candidate models, highlighting its potential as a clinical tool. E-BDL effectively detects salient sub-bands in TFRs, enhancing representation learning and improving the performance and interpretability of DL-based models.

Harmonizing florbetapir and PiB PET measurements of cortical Aß plaque burden using multiple regions-of-interest and machine learning techniques: An alternative to the Centiloid approach.

INTRODUCTION: Machine learning (ML) can optimize amyloid (Aß) comparability among positron emission tomography (PET) radiotracers. Using multi-regional florbetapir (FBP) measures and ML, we report better Pittsburgh compound-B (PiB)/FBP harmonization of mean-cortical Aß (mcAß) than Centiloid. METHODS: PiB-FBP pairs from 92 subjects in www.oasis-brains.org and 46 in www.gaain.org/centiloid-project were used as the training/testing sets. FreeSurfer-extracted FBP multi-regional Aß and actual PiB mcAß in the training set were used to train ML models generating synthetic PiB mcAß. The correlation coefficient (R) between the synthetic/actual PiB mcAß in the testing set was assessed. RESULTS: In the testing set, the synthetic/actual PiB mcAß correlation R = 0.985 (R2  = 0.970) using artificial neural network was significantly higher (p ≤ 6.6e-4) than the FBP/PiB correlation R = 0.927 (R2  = 0.860), improving total variance percentage (R2 ) from 86% to 97%. Other ML models such as partial least square, ensemble, and relevance vector regressions also improved R (p = 9.677e-05 /0.045/0.0017). DISCUSSION: ML improved mcAß comparability. Additional studies are needed for the generalizability to other amyloid tracers, and to tau PET. Highlights Centiloid is a calibration of the amyloid scale, not harmonization. Centiloid unifies the amyloid scale without improving inter-tracer association (R2 ). Machine learning (ML) can harmonize the amyloid scale by improving R2 . ML harmonization maps multi-regional florbetapir SUVRs to PiB mean-cortical SUVR. Artificial neural network ML increases Centiloid R2 from 86% to 97%.

Brain structural and functional abnormalities associated with acute post-traumatic headache: iron deposition and functional connectivity.

BACKGROUND: The purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs, and time since most recent TBI. METHODS: Sixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 90 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons). RESULTS: The acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* in the left posterior cingulate with SCAT symptom severity score (p = 0.05) and T2* in the left cuneus with headache frequency (p = 0.04). CONCLUSIONS: Iron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Defining endogenous TACC3-chTOG-clathrin-GTSE1 interactions at the mitotic spindle using induced relocalization.

A multiprotein complex containing TACC3, clathrin and other proteins has been implicated in mitotic spindle stability. To disrupt this complex in an anti-cancer context, we need to understand its composition and how it interacts with microtubules. Induced relocalization of proteins in cells is a powerful way to analyze protein-protein interactions and, additionally, monitor where and when these interactions occur. We used CRISPR/Cas9 gene editing to add tandem FKBP-GFP tags to each complex member. The relocalization of endogenous tagged protein from the mitotic spindle to mitochondria and assessment of the effect on other proteins allowed us to establish that TACC3 and clathrin are core complex members and that chTOG (also known as CKAP5) and GTSE1 are ancillary to the complex, binding respectively to TACC3 and clathrin, but not each other. We also show that PIK3C2A, a clathrin-binding protein that was proposed to stabilize the TACC3-chTOG-clathrin-GTSE1 complex during mitosis, is not a member of the complex. This work establishes that targeting the TACC3-clathrin interface or their microtubule-binding sites are the two strategies most likely to disrupt spindle stability mediated by this multiprotein complex.

Transcranial direct current stimulation for focal status epilepticus or lateralized periodic discharges in four patients in a critical care setting.

OBJECTIVE: Transcranial direct current stimulation (tDCS) has been advocated for various neurological conditions, including epilepsy. A 1-4-mA cathodal current applied to the scalp over a seizure focus can reduce spikes and seizures. This series of four patients with focal status epilepticus is among the first case series to demonstrate benefit of tDCS in the critical care setting. METHODS: Patients in the intensive care unit were referred for tDCS treatment when focal status epilepticus or clinically relevant lateralized periodic discharges did not resolve with conventional antiseizure medications and anesthetics. Battery-powered direct cathodal current at 2 mA was delivered by an ActivaDose (Caputron) tDCS device via a saline-soaked sponge on the scalp over the seizure focus. Anode was on the contralateral forehead or shoulder. Treatment was for 30 min, repeated twice in a day, then again 1-4 times more over the next few days. RESULTS: Three females and one male, aged 34-68 years, were treated. Etiologies of status epilepticus were posterior reversible encephalopathy syndrome in association with immunosuppressants for a liver transplant, perinatal hypoxic-ischemic injury, a prior cardioembolic parietal stroke, and central nervous system lupus. tDCS led to significant reduction of interictal spikes (.78 to .38/s, p < .0001) in three cases and electrographic seizures (3.83/h to 0/h, p < .001) in two cases. Medication reductions were enabled in all cases subsequent to tDCS. The only side effect of tDCS was transient erythema under the sponge in one case. Two patients died of causes unrelated to tDCS, one was discharged to a nursing home, and one became fully responsive as seizures were controlled with tDCS. SIGNIFICANCE: Spikes and electrographic seizure frequency significantly improved within 1 day of tDCS. Results are potentially confounded by multiple ongoing changes in medications and treatments. These results might encourage further investigation of tDCS in the critical care setting, but verification by controlled studies will be required.

Longitudinal differences in iron deposition in periaqueductal gray matter and anterior cingulate cortex are associated with response to erenumab in migraine.

OBJECTIVES: The objective of this longitudinal study was to determine whether brain iron accumulation, measured using magnetic resonance imaging magnetic transverse relaxation rates (T2*), is associated with response to erenumab for the treatment of migraine. METHODS: Participants (n = 28) with migraine, diagnosed using international classification of headache disorders 3rd edition criteria, were eligible if they had six to 25 migraine days during a four-week headache diary run-in phase. Participants received two treatments with 140 mg erenumab, one immediately following the pre-treatment run-in phase and a second treatment four weeks later. T2* data were collected immediately following the pre-treatment phase, and at two weeks and eight weeks following the first erenumab treatment. Patients were classified as erenumab responders if their migraine-day frequency at five-to-eight weeks post-initial treatment was reduced by at least 50% compared to the pre-treatment run-in phase. A longitudinal Sandwich estimator approach was used to compare longitudinal group differences (responders vs non-responders) in T2* values, associated with iron accumulation. Group visit effects were calculated with a significance threshold of p = 0.005 and cluster forming threshold of 250 voxels. T2* values of 19 healthy controls were used for a reference. The average of each significant region was compared between groups and visits with Bonferroni corrections for multiple comparisons with significance defined as p < 0.05. RESULTS: Pre- and post-treatment longitudinal imaging data were available from 28 participants with migraine for a total of 79 quantitative T2* images. Average subject age was 42 ± 13 years (25 female, three male). Of the 28 subjects studied, 53.6% were erenumab responders. Comparing longitudinal T2* between erenumab responders vs non-responders yielded two comparisons which survived the significance threshold of p < 0.05 after correction for multiple comparisons: the difference at eight weeks between the erenumab-responders and non-responders in the periaqueductal gray (mean ± standard error; responders 43 ± 1 ms vs non-responders 32.5 ± 1 ms, p = 0.002) and the anterior cingulate cortex (mean ± standard error; responders 50 ± 1 ms vs non-responders 40 ± 1 ms, p = 0.01). CONCLUSIONS: Erenumab response is associated with higher T2* in the periaqueductal gray and anterior cingulate cortex, regions that participate in pain processing and modulation. T2* differences between erenumab responders vs non-responders, a measure of brain iron accumulation, are seen at eight weeks post-treatment. Less iron accumulation in the periaqueductal gray and anterior cingulate cortex might play a role in the therapeutic mechanisms of migraine reduction associated with erenumab.

Questionnaire and structural imaging data accurately predict headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury.

BACKGROUND: Our prior work demonstrated that questionnaires assessing psychosocial symptoms have utility for predicting improvement in patients with acute post-traumatic headache following mild traumatic brain injury. In this cohort study, we aimed to determine whether prediction accuracy can be refined by adding structural magnetic resonance imaging (MRI) brain measures to the model. METHODS: Adults with acute post-traumatic headache (enrolled 0-59 days post-mild traumatic brain injury) underwent T1-weighted brain MRI and completed three questionnaires (Sports Concussion Assessment Tool, Pain Catastrophizing Scale, and the Trait Anxiety Inventory Scale). Individuals with post-traumatic headache completed an electronic headache diary allowing for determination of headache improvement at three- and at six-month follow-up. Questionnaire and MRI measures were used to train prediction models of headache improvement and headache trajectory. RESULTS: Forty-three patients with post-traumatic headache (mean age = 43.0, SD = 12.4; 27 females/16 males) and 61 healthy controls were enrolled (mean age = 39.1, SD = 12.8; 39 females/22 males). The best model achieved cross-validation Area Under the Curve of 0.801 and 0.805 for predicting headache improvement at three and at six months. The top contributing MRI features for the prediction included curvature and thickness of superior, middle, and inferior temporal, fusiform, inferior parietal, and lateral occipital regions. Patients with post-traumatic headache who did not improve by three months had less thickness and higher curvature measures and notably greater baseline differences in brain structure vs. healthy controls (thickness: p < 0.001, curvature: p = 0.012) than those who had headache improvement. CONCLUSIONS: A model including clinical questionnaire data and measures of brain structure accurately predicted headache improvement in patients with post-traumatic headache and achieved improvement compared to a model developed using questionnaire data alone.

Thalamic subfield iron accumulation after acute mild traumatic brain injury as a marker of future post-traumatic headache intensity.

OBJECTIVE: To explore alterations in thalamic subfield volume and iron accumulation in individuals with post-traumatic headache (PTH) relative to healthy controls. BACKGROUND: The thalamus plays a pivotal role in the pathomechanism of pain and headache, yet the role of the thalamus in PTH attributed to mild traumatic brain injury (mTBI) remains unclear. METHODS: A total of 107 participants underwent multimodal T1-weighted and T2* brain magnetic resonance imaging. Using a clinic-based observational study, thalamic subfield volume and thalamic iron accumulation were explored in 52 individuals with acute PTH (mean age = 41.3; standard deviation [SD] = 13.5), imaged on average 24 days post mTBI, and compared to 55 healthy controls (mean age = 38.3; SD = 11.7) without history of mTBI or migraine. Symptoms of mTBI and headache characteristics were assessed at baseline (0-59 days post mTBI) (n = 52) and 3 months later (n = 46) using the Symptom Evaluation of the Sports Concussion Assessment Tool (SCAT-5) and a detailed headache history questionnaire. RESULTS: Relative to controls, individuals with acute PTH had significantly less volume in the lateral geniculate nucleus (LGN) (mean volume: PTH = 254.1, SD = 43.4 vs. controls = 278.2, SD = 39.8; p = 0.003) as well as more iron deposition in the left LGN (PTH: T2* signal = 38.6, SD = 6.5 vs. controls: T2* signal = 45.3, SD = 2.3; p = 0.048). Correlations in individuals with PTH revealed a positive relationship between left LGN T2* iron deposition and SCAT-5 symptom severity score at baseline (r = -0.29, p = 0.019) and maximum headache intensity at the 3-month follow-up (r = -0.47, p = 0.002). CONCLUSION: Relative to healthy controls, individuals with acute PTH had less volume and higher iron deposition in the left LGN. Higher iron deposition in the left LGN might reflect mTBI severity and poor headache recovery.

Use of novel structural features to identify urinary biomarkers during acute kidney injury that predict progression to chronic kidney disease.

BACKGROUND: A significant barrier to biomarker development in the field of acute kidney injury (AKI) is the use of kidney function to identify candidates. Progress in imaging technology makes it possible to detect early structural changes prior to a decline in kidney function. Early identification of those who will advance to chronic kidney disease (CKD) would allow for the initiation of interventions to halt progression. The goal of this study was to use a structural phenotype defined by magnetic resonance imaging and histology to advance biomarker discovery during the transition from AKI to CKD. METHODS: Urine was collected and analyzed from adult C57Bl/6 male mice at four days and 12 weeks after folic acid-induced AKI. Mice were euthanized 12 weeks after AKI and structural metrics were obtained from cationic ferritin-enhanced-MRI (CFE-MRI) and histologic assessment. The fraction of proximal tubules, number of atubular glomeruli (ATG), and area of scarring were measured histologically. The correlation between the urinary biomarkers at the AKI or CKD and CFE-MRI derived features was determined, alone or in combination with the histologic features, using principal components. RESULTS: Using principal components derived from structural features, twelve urinary proteins were identified at the time of AKI that predicted structural changes 12 weeks after injury. The raw and normalized urinary concentrations of IGFBP-3 and TNFRII strongly correlated to the structural findings from histology and CFE-MRI. Urinary fractalkine concentration at the time of CKD correlated with structural findings of CKD. CONCLUSIONS: We have used structural features to identify several candidate urinary proteins that predict whole kidney pathologic features during the transition from AKI to CKD, including IGFBP-3, TNFRII, and fractalkine. In future work, these biomarkers must be corroborated in patient cohorts to determine their suitability to predict CKD after AKI.

STRIDE: Systematic Radar Intelligence Analysis for ADRD Risk Evaluation with Gait Signature Simulation and Deep Learning.

Abnormal gait is a significant non-cognitive biomarker for Alzheimer's disease (AD) and AD-related dementia (ADRD). Micro-Doppler radar, a non-wearable technology, can capture human gait movements for potential early ADRD risk assessment. In this research, we propose to design STRIDE integrating micro-Doppler radar sensors with advanced artificial intelligence (AI) technologies. STRIDE embeds a new deep learning (DL) classification framework. As a proof of concept, we develop a "digital-twin" of STRIDE, consisting of a human walking simulation model and a micro-Doppler radar simulation model, to generate a gait signature dataset. Taking established human walking parameters, the walking model simulates individuals with ADRD under various conditions. The radar model based on electromagnetic scattering and the Doppler frequency shift model is employed to generate micro-Doppler signatures from different moving body parts (e.g., foot, limb, joint, torso, shoulder, etc.). A band-dependent DL framework is developed to predict ADRD risks. The experimental results demonstrate the effectiveness and feasibility of STRIDE for evaluating ADRD risk.

Corrections to "STRIDE: Systematic Radar Intelligence Analysis for ADRD Risk Evaluation with Gait Signature Simulation and Deep Learning".

[This corrects the article PMC10399976.].

T2* reduction in patients with acute post-traumatic headache.

OBJECTIVES: Although iron accumulation in pain-processing brain regions has been associated with repeated migraine attacks, brain structural changes associated with post-traumatic headache have yet to be elucidated. To determine whether iron accumulation is associated with acute post-traumatic headache, magnetic resonance transverse relaxation rates (T2*) associated with iron accumulation were investigated between individuals with acute post-traumatic headache attributed to mild traumatic brain injury and healthy controls. METHODS: Twenty individuals with acute post-traumatic headache and 20 age-matched healthy controls underwent 3T brain magnetic resonance imaging including quantitative T2* maps. T2* differences between individuals with post-traumatic headache versus healthy controls were compared using age-matched paired t-tests. Associations of T2* values with headache frequency and number of mild traumatic brain injuries were investigated using multiple linear regression in individuals with post-traumatic headache. Significance was determined using uncorrected p-value and cluster size threshold. RESULTS: Individuals with post-traumatic headache had lower T2* values compared to healthy controls in cortical (bilateral frontal, bilateral anterior and posterior cingulate, right postcentral, bilateral temporal, right supramarginal, right rolandic, left insula, left occipital, right parahippocampal), subcortical (left putamen, bilateral hippocampal) and brainstem regions (pons). Within post-traumatic headache subjects, multiple linear regression showed a negative association between T2* in the right inferior parietal/supramarginal regions and number of mild traumatic brain injuries and a negative association between T2* in bilateral cingulate, bilateral precuneus, bilateral supplementary motor areas, bilateral insula, right middle temporal and right lingual areas and headache frequency. CONCLUSIONS: Acute post-traumatic headache is associated with iron accumulation in multiple brain regions. Correlations with headache frequency and number of lifetime mild traumatic brain injuries suggest that iron accumulation is part of the pathophysiology or a marker of mild traumatic brain injury and post-traumatic headache.

Deep residual inception encoder-decoder network for amyloid PET harmonization.

INTRODUCTION: Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy. METHOD: A Residual Inception Encoder-Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound-B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10-fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects. RESULTS: Significantly stronger between-tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel-wise measurements in the training cohort and the external testing cohort. DISCUSSION: We proposed and validated a novel encoder-decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers.

Occupant health in buildings: Impact of the COVID-19 pandemic on the opinions of building professionals and implications on research.

The objectives of this study are to investigate building professionals' experience, awareness, and interest in occupant health in buildings, and to assess the impact of the COVID-19 pandemic on their opinions, as well as to compare the research on occupant health in buildings to professionals' opinions. To address these objectives, a mixed research methodology, including a thorough review of the literature (NL = 190) and an online survey (NS = 274), was utilized. In general, there is an increasing research interest in occupant health and a heightened interest in health-related projects, among professionals, following the COVID-19 pandemic. Specifically, among the nine different building attributes examined, indoor air quality was the most researched building attribute with a focus on occupant health and was also presumed to be the most important by the professionals. Professionals considered fatigue and musculoskeletal pain to be the most important physical well-being issues, and stress, anxiety, and depression to be the most important mental well-being issues that need to be the focus of design, construction, and operation of buildings to support and promote occupant health, while eye-related symptoms and loss of concentration were the most researched physical and mental well-being symptoms in the literature, respectively. Finally, professionals indicated that COVID-19 pandemic had significant effect on their perspectives regarding buildings' impact on occupant health and they believed future building design, construction and operation will focus more on occupant health because of the pandemic experience.

Longitudinal changes in functional connectivity and pain-induced brain activations in patients with migraine: a functional MRI study pre- and post- treatment with Erenumab.

BACKGROUND: Migraine involves central and peripheral nervous system mechanisms. Erenumab, an anti-calcitonin gene-related peptide (CGRP) receptor monoclonal antibody with little central nervous system penetrance, is effective for migraine prevention. The objective of this study was to determine if response to erenumab is associated with alterations in brain functional connectivity and pain-induced brain activations. METHODS: Adults with 6-25 migraine days per month during a 4-week headache diary run-in phase underwent pre-treatment brain functional MRI (fMRI) that included resting-state functional connectivity and BOLD measurements in response to moderately painful heat stimulation to the forearm. This was followed by two treatments with 140 mg erenumab, at baseline and 4 weeks later. Post-treatment fMRI was performed 2 weeks and 8 weeks following the first erenumab treatment. A longitudinal Sandwich estimator analysis was used to identify pre- to post-treatment changes in resting-state functional connectivity and brain activations in response to thermal pain. fMRI findings were compared between erenumab treatment-responders vs. erenumab non-responders. RESULTS: Pre- and post-treatment longitudinal imaging data were available from 32 participants. Average age was 40.3 (+/- 13) years and 29 were female. Pre-treatment average migraine day frequency was 13.8 (+/- 4.7) / 28 days and average headache day frequency was 15.8 (+/- 4.4) / 28 days. Eighteen of 32 (56%) were erenumab responders. Compared to erenumab non-responders, erenumab responders had post-treatment differences in 1) network functional connectivity amongst pain-processing regions, including higher global efficiency, clustering coefficient, node degree, regional efficiency, and modularity, 2) region-to-region functional connectivity between several regions including temporal pole, supramarginal gyrus, and hypothalamus, and 3) pain-induced activations in the middle cingulate, posterior cingulate, and periaqueductal gray matter. CONCLUSIONS: Reductions in migraine day frequency accompanying erenumab treatment are associated with changes in resting state functional connectivity and central processing of extracranial painful stimuli that differ from erenumab non-responders. TRIAL REGISTRATION: clinicaltrials.gov (NCT03773562).