Do time preferences predict diabetes outcomes? A combined survey and register-based study.

Identifying determinants of heterogeneity in health outcomes continues to be a focus in the health economic literature. In this study, we analyze whether time preferences predict health outcomes in individuals with type 1 diabetes (T1D) who use insulin pump therapy to manage their condition. We collect data on time preferences using a hypothetical matching task and estimate aggregate as well as individual-level discounting parameters using the exponential, hyperbolic, and quasi-hyperbolic discounting models. These parameters are then regressed against essential diabetes-related health outcomes obtained from registries and medical records, including glycemic control, kidney function, BMI, and number of hospital contacts. Our analyses indicate that all three discounting models fit the data equally well. Except for hospital contacts, we find robust evidence that impatience, as reflected by higher discounting, predicts worse health outcomes. Additionally, present bias is associated with worse kidney function. Our findings suggest that time preferences can explain some of the heterogeneity in health among individuals with T1D and call for increased attention on the role of time preferences in the design of disease management programs for individuals with chronic conditions.

Prior-guided individualized thalamic parcellation based on local diffusion characteristics.

Comprising numerous subnuclei, the thalamus intricately interconnects the cortex and subcortex, orchestrating various facets of brain functions. Extracting personalized parcellation patterns for these subnuclei is crucial, as different thalamic nuclei play varying roles in cognition and serve as therapeutic targets for neuromodulation. However, accurately delineating the thalamic nuclei boundary at the individual level is challenging due to intersubject variability. In this study, we proposed a prior-guided parcellation (PG-par) method to achieve robust individualized thalamic parcellation based on a central-boundary prior. We first constructed probabilistic atlas of thalamic nuclei using high-quality diffusion MRI datasets based on the local diffusion characteristics. Subsequently, high-probability voxels in the probabilistic atlas were utilized as prior guidance to train unique multiple classification models for each subject based on a multilayer perceptron. Finally, we employed the trained model to predict the parcellation labels for thalamic voxels and construct individualized thalamic parcellation. Through a test-retest assessment, the proposed prior-guided individualized thalamic parcellation exhibited excellent reproducibility and the capacity to detect individual variability. Compared with group atlas registration and individual clustering parcellation, the proposed PG-par demonstrated superior parcellation performance under different scanning protocols and clinic settings. Furthermore, the prior-guided individualized parcellation exhibited better correspondence with the histological staining atlas. The proposed prior-guided individualized thalamic parcellation method contributes to the personalized modeling of brain parcellation.

Associations between use of diabetes technology and diabetes distress: a Danish cross-sectional survey of adults with type 1 diabetes.

INTRODUCTION: The study aimed to investigate independent and combined associations between insulin delivery method (insulin pump therapy (IPT) vs multiple daily injections (MDI)), glucose monitoring method (intermittently scanned continuous glucose monitoring (isCGM) and real-time continuous glucose monitoring (rtCGM) vs blood glucose metre (BGM)) and diabetes distress (DD) in adults with type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: We combined data from two Danish questionnaire-based surveys, the Steno Tech Survey (n=1591) and the Type 1 Diabetes Distress Scale (T1-DDS) validation survey (n=4205), in which individuals aged ≥18 years with T1D were invited to participate. The 28-item T1-DDS was used to measure DD and DD scores were categorised as little or no distress (score <2.0), moderate distress (2.0-2.9) and high distress (score ≥3.0). Associations between insulin delivery, glucose monitoring methods and DD were assessed using linear regression. RESULTS: Among 2068 adults with T1D who responded to one of the surveys, the use of IPT was associated with a lower total T1-DDS score (-0.09, 95% CI 0.16 to -0.03) compared with MDI and adjusted for glucose monitoring method. The use of CGM was associated with a higher total T1-DDS score (0.11, 95% CI 0.05 to 0.18) compared with BGM and adjusted for the insulin delivery method. IPT was still associated with a lower T1-DDS score, regardless of being combined with BGM (-0.17, 95% CI -0.28 to -0.06) or CGM (-0.13, 95% CI -0.21 to -0.05), compared with MDI with CGM. No association was found between the type of CGM (isCGM vs rtCGM) and DD among either IPT or MDI users when restricting analysis to individuals using CGM. CONCLUSIONS: Among Danish adults with T1D, the use of IPT was associated with lower levels of DD, while CGM use was associated with higher levels of DD. DD should be addressed when introducing people with T1D to diabetes technology, CGM in particular. TRIAL REGISTRATION NUMBER: NCT04311164 (Results).

Spatio-molecular profiles shape the human cerebellar hierarchy along the sensorimotor-association axis.

Cerebellar involvement in both motor and non-motor functions manifests in specific regions of the human cerebellum, revealing the functional heterogeneity within it. One compelling theory places the heterogeneity within the cerebellar functional hierarchy along the sensorimotor-association (SA) axis. Despite extensive neuroimaging studies, evidence for the cerebellar SA axis from different modalities and scales was lacking. Thus, we establish a significant link between the cerebellar SA axis and spatio-molecular profiles. Utilizing the gene set variation analysis, we find the intermediate biological principles the significant genes leveraged to scaffold the cerebellar SA axis. Interestingly, we find these spatio-molecular profiles notably associated with neuropsychiatric dysfunction and recent evolution. Furthermore, cerebello-cerebral interactions at genetic and functional connectivity levels mirror the cerebral cortex and cerebellum's SA axis. These findings can provide a deeper understanding of how the human cerebellar SA axis is shaped and its role in transitioning from sensorimotor to association functions.

Electroconvulsive therapy disrupts functional connectivity between hippocampus and posterior default mode network.

BACKGROUND: The mechanisms underlying memory deficits after electroconvulsive therapy (ECT) remain unclear but altered functional interactions between hippocampus and neocortex may play a role. OBJECTIVES: To test whether ECT reduces functional connectivity between hippocampus and posterior regions of the default mode network (DMN) and to examine whether altered hippocampal-neocortical functional connectivity correlates with memory impairment. A secondary aim was to explore if these connectivity changes are present 6 months after ECT. METHODS: In-patients with severe depression (n = 35) received bitemporal ECT. Functional connectivity of the hippocampus was probed with resting-state fMRI before the first ECT-session, after the end of ECT, and at a six-month follow-up. Memory was assessed with the Verbal Learning Test - Delayed Recall. Seed-based connectivity analyses established connectivity of four hippocampal seeds, covering the anterior and posterior parts of the right and left hippocampus. RESULTS: Compared to baseline, three of four hippocampal seeds became less connected to the core nodes of the posterior DMN in the week after ECT with Cohen's d ranging from -0.9 to -1.1. At the group level, patients showed post-ECT memory impairment, but individual changes in delayed recall were not correlated with the reduction in hippocampus-DMN connectivity. At six-month follow-up, no significant hippocampus-DMN reductions in connectivity were evident relative to pre-ECT, and memory scores had returned to baseline. CONCLUSION: ECT leads to a temporary disruption of functional hippocampus-DMN connectivity in patients with severe depression, but the change in connectivity strength is not related to the individual memory impairment.

End-to-end volumetric segmentation of white matter hyperintensities using deep learning.

BACKGROUND AND OBJECTIVES: Reliable detection of white matter hyperintensities (WMH) is crucial for studying the impact of diffuse white-matter pathology on brain health and monitoring changes in WMH load over time. However, manual annotation of 3D high-dimensional neuroimages is laborious and can be prone to biases and errors in the annotation procedure. In this study, we evaluate the performance of deep learning (DL) segmentation tools and propose a novel volumetric segmentation model incorporating self-attention via a transformer-based architecture. Ultimately, we aim to evaluate diverse factors that influence WMH segmentation, aiming for a comprehensive analysis of the state-of-the-art algorithms in a broader context. METHODS: We trained state-of-the-art DL algorithms, and incorporated advanced attention mechanisms, using structural fluid-attenuated inversion recovery (FLAIR) image acquisitions. The anatomical MRI data utilized for model training was obtained from healthy individuals aged 62-70 years in the Live active Successful Aging (LISA) project. Given the potential sparsity of lesion volume among healthy aging individuals, we explored the impact of incorporating a weighted loss function and ensemble models. To assess the generalizability of the studied DL models, we applied the trained algorithm to an independent subset of data sourced from the MICCAI WMH challenge (MWSC). Notably, this subset had vastly different acquisition parameters compared to the LISA dataset used for training. RESULTS: Consistently, DL approaches exhibited commendable segmentation performance, achieving the level of inter-rater agreement comparable to expert performance, ensuring superior quality segmentation outcomes. On the out of sample dataset, the ensemble models exhibited the most outstanding performance. CONCLUSIONS: DL methods generally surpassed conventional approaches in our study. While all DL methods performed comparably, incorporating attention mechanisms could prove advantageous in future applications with a wider availability of training data. As expected, our experiments indicate that the use of ensemble-based models enables the superior generalization in out-of-distribution settings. We believe that introducing DL methods in the WHM annotation workflow in heathy aging cohorts is promising, not only for reducing the annotation time required, but also for eventually improving accuracy and robustness via incorporating the automatic segmentations in the evaluation procedure.

Brain stimulation with 40 Hz heterochromatic flicker extended beyond red, green, and blue.

Alzheimer's disease (AD) is associated with electrophysiological changes in the brain. Pre-clinical and early clinical trials have shown promising results for the possible therapy of AD with 40 Hz neurostimulation. The most notable findings used stroboscopic flicker, but this technique poses an inherent barrier for human applications due to its visible flickering and resulting high level of perceived discomfort. Therefore, alternative options should be investigated for entraining 40 Hz brain activity with light sources that appear less flickering. Previously, chromatic flicker based on red, green, and blue (RGB) have been studied in the context of brain-computer interfaces, but this is an incomplete representation of the colours in the visual spectrum. This study introduces a new kind of heterochromatic flicker based on spectral combinations of blue, cyan, green, lime, amber, and red (BCGLAR). These combinations are investigated by the steady-state visually evoked potential (SSVEP) response from the flicker with an aim of optimising the choice of 40 Hz light stimulation with spectrally similar colour combinations in BCGLAR space. Thirty healthy young volunteers were stimulated with heterochromatic flicker in an electroencephalography experiment with randomised complete block design. Responses were quantified as the 40 Hz signal-to-noise ratio and analysed using mixed linear models. The size of the SSVEP response to heterochromatic flicker is dependent on colour combinations and influenced by both visual and non-visual effects. The amber-red flicker combination evoked the highest SSVEP, and combinations that included blue and/or red consistently evoked higher SSVEP than combinations only with mid-spectrum colours. Including a colour from either extreme of the visual spectrum (blue and/or red) in at least one of the dyadic phases appears to be more important than choosing pairs of colours that are far from each other on the visual spectrum. Spectrally adjacent colour pairs appear less flickering to the perceiver, and thus the results motivate investigations into the limits for how alike the two phases can be and still evoke a 40 Hz response. Specifically, combining a colour on either extreme of the visual spectrum with another proximal colour might provide the best trade-off between flickering sensation and SSVEP magnitude.

Individualized brain mapping for navigated neuromodulation.

ABSTRACT: The brain is a complex organ that requires precise mapping to understand its structure and function. Brain atlases provide a powerful tool for studying brain circuits, discovering biological markers for early diagnosis, and developing personalized treatments for neuropsychiatric disorders. Neuromodulation techniques, such as transcranial magnetic stimulation and deep brain stimulation, have revolutionized clinical therapies for neuropsychiatric disorders. However, the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques. Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems. Still, the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions. The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles, advantages, disadvantages, and future trends of these techniques. The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

Lack of reproducibility of resting-state functional MRI findings in migraine with aura.

BACKGROUND: Several studies have applied resting-state functional MRI to examine whether functional brain connectivity is altered in migraine with aura patients. These studies had multiple limitations, including small sample sizes, and reported conflicting results. Here, we performed a large, cross-sectional brain imaging study to reproduce previous findings. METHODS: We recruited women aged 30-60 years from the nationwide Danish Twin Registry. Resting-state functional MRI of women with migraine with aura, their co-twins, and unrelated migraine-free twins was performed at a single centre. We carried out an extensive series of brain connectivity data analyses. Patients were compared to migraine-free controls and to co-twins. RESULTS: Comparisons were based on data from 160 patients, 30 co-twins, and 136 controls. Patients were similar to controls with regard to age, and several lifestyle characteristics. We replicated clear effects of age on resting-state networks. In contrast, we failed to detect any differences, and to replicate previously reported differences, in functional connectivity between migraine patients with aura and non-migraine controls or their co-twins in any of the analyses. CONCLUSION: Given the large sample size and the unbiased population-based design of our study, we conclude that women with migraine with aura have normal resting-state brain connectivity outside of migraine attacks.

Study on the effect of 40 Hz non-invasive light therapy system. A protocol for a randomized, double-blinded, placebo-controlled clinical trial.

Introduction: With no cure or effective treatment, the prevalence of patients with Alzheimer's disease (AD) is expected to intensify, thereby increasing the social and financial burden on society. Light-based 40 Hz brain stimulation is considered a novel treatment strategy for patients with AD that may alleviate some of this burden. The clinical trial ALZLIGHT will utilize a novel Light Therapy System (LTS). The LTS uses Invisible Spectral Flicker for non-invasive induction of 40 Hz neural activity. This protocol describes a trial evaluating the efficacy and safety of a light-based 40 Hz brain stimulation in patients with mild-to-moderate AD. Methods: 62 patients with mild-to-moderate AD will participate in a randomized, double-blinded, placebo-controlled, parallel-group, and single-center trial. The participants will partake in an enrollment period of 1 month, an intervention period of 6 months, and a 1.5-month post-interventional follow-up period. Prior to the baseline measurement (week 0), the patients will be randomized to either active or placebo intervention from baseline (week 0) to post-intervention follow-up (week 26). Discussion: This protocol describes a randomized, double-blinded, placebo-controlled clinical trial that may increase the understanding of the effect of gamma oscillations in the human brain and how it could be utilized as a novel and important tool for the treatment of AD. The effect is measured through a large, multidisciplinary assessment battery.Clinical trial registration:www.ClinicalTrials.gov, (NCT05260177). Registered on March 2, 2022.

Executive Control and Associated Brain Activity in Children With Familial High-Risk of Schizophrenia or Bipolar Disorder: A Danish Register-based Study.

BACKGROUND AND HYPOTHESES: Impaired executive control is a potential prognostic and endophenotypic marker of schizophrenia (SZ) and bipolar disorder (BP). Assessing children with familial high-risk (FHR) of SZ or BP enables characterization of early risk markers and we hypothesize that they express impaired executive control as well as aberrant brain activation compared to population-based control (PBC) children. STUDY DESIGN: Using a flanker task, we examined executive control together with functional magnetic resonance imaging (fMRI) in 11- to 12-year-old children with FHR of SZ (FHR-SZ) or FHR of BP (FHR-BP) and PBC children as part of a register-based, prospective cohort-study; The Danish High Risk and Resilience study-VIA 11. STUDY RESULTS: We included 85 (44% female) FHR-SZ, 63 (52% female) FHR-BP and 98 (50% female) PBC in the analyses. Executive control effects, caused by the spatial visuomotor conflict, showed no differences between groups. Bayesian ANOVA of reaction time (RT) variability, quantified by the coefficient of variation (CVRT), revealed a group effect with similarly higher CVRT in FHR-BP and FHR-SZ compared to PBC (BF10 = 6.82). The fMRI analyses revealed no evidence for between-group differences in task-related brain activation. Post hoc analyses excluding children with psychiatric illness yielded same results. CONCLUSION: FHR-SZ and FHR-BP at age 11-12 show intact ability to resolve a spatial visuomotor conflict and neural efficacy. The increased variability in RT may reflect difficulties in maintaining sustained attention. Since variability in RT was independent of existing psychiatric illness, it may reflect a potential endophenotypic marker of risk.

Evaluating the influence of anatomical accuracy and electrode positions on EEG forward solutions.

Generating realistic volume conductor models for forward calculations in electroencephalography (EEG) is not trivial and several factors contribute to the accuracy of such models, two of which are its anatomical accuracy and the accuracy with which electrode positions are known. Here, we investigate effects of anatomical accuracy by comparing forward solutions from SimNIBS, a tool which allows state-of-the-art anatomical modeling, with well-established pipelines in MNE-Python and FieldTrip. We also compare different ways of specifying electrode locations when digitized positions are not available such as transformation of measured positions from standard space and transformation of a manufacturer layout. Substantial effects of anatomical accuracy were seen throughout the entire brain both in terms of field topography and magnitude with SimNIBS generally being more accurate than the pipelines in MNE-Python and FieldTrip. Topographic and magnitude effects were particularly pronounced for MNE-Python which uses a three-layer boundary element method (BEM) model. We attribute these mainly to the coarse representation of the anatomy used in this model, in particular differences in skull and cerebrospinal fluid (CSF). Effects of electrode specification method were evident in occipital and posterior areas when using a transformed manufacturer layout whereas transforming measured positions from standard space generally resulted in smaller errors. We suggest modeling the anatomy of the volume conductor as accurately possible and we hope to facilitate this by making it easy to export simulations from SimNIBS to MNE-Python and FieldTrip for further analysis. Likewise, if digitized electrode positions are not available, a set of measured positions on a standard head template may be preferable to those specified by the manufacturer.

Investigations of the subarachnoid space as a potential link between aura and headache in migraine: A case-control MRI study.

BACKGROUND: The connection between migraine aura and headache is poorly understood. Some patients experience migraine aura without headache, and patients with migraine aura with headache commonly experience milder headaches with age. The distance between the cerebral cortex and the overlying dura mater has been hypothesized to influence development of headache following aura. We tested this hypothesis by comparing approximated distances between visual cortical areas and overlying dura mater between female patients with migraine aura without headache and female patients with migraine aura with headache. METHODS: Twelve cases with migraine aura without headache and 45 age-matched controls with migraine aura with headache underwent 3.0 T MRI. We calculated average distances between the occipital lobes, between the calcarine sulci, and between the skull and visual areas V1, V2 and V3a. We also measured volumes of corticospinal fluid between the occipital lobes, between the calcarine sulci, and overlying visual areas V2 and V3a. We investigated the relationship between headache status, distances and corticospinal fluid volumes using conditional logistic regression. RESULTS: Distances between the occipital lobes, calcarine sulci and between the skull and V1, V2 and V3a did not differ between patients with migraine aura with headache and patients with migraine aura without headache. We found no differences in corticospinal fluid volumes between groups. CONCLUSION: We found no indication for a connection between visual migraine aura and headache based on cortico-cortical, cortex-to-skull distances, or corticospinal fluid volumes overlying visual cortical areas. Longitudinal studies with imaging sequences optimized for measuring the cortico-dural distance and a larger sample of patients are needed to further investigate the hypothesis.

Dynamic involvement of premotor and supplementary motor areas in bimanual pinch force control.

Many activities of daily living require quick shifts between symmetric and asymmetric bimanual actions. Bimanual motor control has been mostly studied during continuous repetitive tasks, while little research has been carried out in experimental settings requiring dynamic changes in motor output generated by both hands. Here, we performed functional magnetic resonance imaging (MRI) while healthy volunteers performed a visually guided, bimanual pinch force task. This enabled us to map functional activity and connectivity of premotor and motor areas during bimanual pinch force control in different task contexts, requiring mirror-symmetric or inverse-asymmetric changes in discrete pinch force exerted with the right and left hand. The bilateral dorsal premotor cortex showed increased activity and effective coupling to the ipsilateral supplementary motor area (SMA) in the inverse-asymmetric context compared to the mirror-symmetric context of bimanual pinch force control while the SMA showed increased negative coupling to visual areas. Task-related activity of a cluster in the left caudal SMA also scaled positively with the degree of synchronous initiation of bilateral pinch force adjustments, irrespectively of the task context. The results suggest that the dorsal premotor cortex mediates increasing complexity of bimanual coordination by increasing coupling to the SMA while SMA provides feedback about motor actions to the sensory system.

Associations between clinical and psychosocial factors and HbA1c in adult insulin pump users with type 1 diabetes.

AIMS: Many adults with type 1 diabetes do not achieve recommended glycemic goals despite intensive insulin therapy using insulin pumps. The aim of this study was to explore associations between clinical and psychosocial factors and HbA1c in insulin pump users to identify and prioritize areas for potential intervention. METHODS: A questionnaire-based survey covering clinical and psychosocial aspects of life with type 1 diabetes was distributed to all adult (≥ 18 years) insulin pump users in the Capital Region of Denmark. Responses were combined with data from medical records and national registries. Associations with HbA1c were modeled using regression-based machine learning. RESULTS: Of 1,591 invited individuals, 770 (48.4%) responded to the survey. Mean HbA1c among responders was 7.3% (56 mmol/mmol), and 35.6% had an HbA1c < 7.0% (53 mmol/mol). Six factors were significantly associated with HbA1c: diabetes duration (0.006% (0.1 mmol/mol) lower HbA1c per 1-year increase in diabetes duration); education (0.4% (4.3 mmol/mol) lower HbA1c with long higher education vs. primary school); insulin type (0.2% (2.2 mmol/mol) lower HbA1c with ultra-rapid-acting insulin vs. rapid-acting insulin); hypoglycemia awareness status (0.2% (2.2 mmol/mol) lower HbA1c with complete unawareness vs. full awareness); insulin device satisfaction (0.2% (2.7 mmol/mol) lower HbA1c per 1-point increase in Insulin Device Satisfaction Survey score); and diabetes distress (0.3% (3.1 mmol/mol) higher HbA1c per 1-point increase in Type 1 Diabetes Distress Scale score). CONCLUSIONS: This study identified several associations between clinical and psychosocial factors and HbA1c that may be considered when developing interventions targeted people with type 1 diabetes.

Safety, Feasibility, and Potential Clinical Efficacy of 40 Hz Invisible Spectral Flicker versus Placebo in Patients with Mild-to-Moderate Alzheimer's Disease: A Randomized, Placebo-Controlled, Double-Blinded, Pilot Study.

BACKGROUND: Recent studies suggested induction of 40 Hz neural activity as a potential treatment for Alzheimer's disease (AD). However, prolonged exposure to flickering light raises adherence and safety concerns, encouraging investigation of tolerable light stimulation protocols. OBJECTIVE: To investigate the safety, feasibility, and exploratory measures of efficacy. METHODS: This two-stage randomized placebo-controlled double-blinded clinical trial, recruited first cognitive healthy participants (n = 3/2 active/placebo), and subsequently patients with mild-to-moderate AD (n = 5/6, active/placebo). Participants were randomized 1:1 to receive either active intervention with 40 Hz Invisible Spectral Flicker (ISF) or placebo intervention with color and intensity matched non-flickering white light. RESULTS: Few and mild adverse events were observed. Adherence was above 86.1% of intended treatment days, with participants remaining in front of the device for >51.3 min (60 max) and directed gaze >34.9 min. Secondary outcomes of cognition indicate a tendency towards improvement in the active group compared to placebo (mean: -2.6/1.5, SD: 6.58/6.53, active/placebo) at week 6. Changes in hippocampal and ventricular volume also showed no tendency of improvement in the active group at week 6 compared to placebo. At week 12, a potential delayed effect of the intervention was seen on the volume of the hippocampus in the active group compared to placebo (mean: 0.34/-2.03, SD: 3.26/1.18, active/placebo), and the ventricular volume active group (mean: -0.36/2.50, SD: 1.89/2.05, active/placebo), compared to placebo. CONCLUSION: Treatment with 40 Hz ISF offers no significant safety or adherence concerns. Potential impact on secondary outcomes must be tested in larger scale clinical trials.

Associations between insulin pump self-management and HbA1c in type 1 diabetes.

AIMS: Insulin pump self-management is important for glycaemic outcomes. We aimed to investigate associations between self-management factors and HbA1c. METHODS: Adult insulin pump users with type 1 diabetes (n = 770) completed an online questionnaire. The latest HbA1c and demographics were extracted from national registries. Associations between HbA1c and self-management (use of advanced features, timing of infusion set change, timing of meal bolus, data-upload and pump settings adjustments) were investigated using backward selected linear regression models. RESULTS: Of the 699 responders eligible for this study, 60% were women; the median age and diabetes duration were 49 and 25 years, respectively. Significant associations with HbA1c were found for changing infusion set every 0-4 days relative to 5-10 days (-5 mmol/mol (-0.4%), p = 0.003), and for never/rarely missing a bolus (-6 mmol/mol (-0.5%), p < 0.001) relative to often missing a bolus. Timing insulin 10-15 min before meal relative to after meal start was also associated with lower HbA1c (-3 mmol/mol (-0.3%), p = 0.023). Self-adjusting pump settings showed the strongest association with lower HbA1c (-6 mmol/mol (-0.6%), p < 0.001) relative to health care professionals doing all adjustments. CONCLUSION: Self-adjusting insulin pump settings, optimal timing and few omissions of meal boluses, and timely change of infusion set are associated with lower HbA1c.

Decomposition-based framework for tumor classification and prediction of treatment response from longitudinal MRI.

Objective.In the field of radiation oncology, the benefit of MRI goes beyond that of providing high soft-tissue contrast images for staging and treatment planning. With the recent clinical introduction of hybrid MRI linear accelerators it has become feasible to map physiological parameters describing diffusion, perfusion, and relaxation during the entire course of radiotherapy, for example. However, advanced data analysis tools are required for extracting qualified prognostic and predictive imaging biomarkers from longitudinal MRI data. In this study, we propose a new prediction framework tailored to exploit temporal dynamics of tissue features from repeated measurements. We demonstrate the framework using a newly developed decomposition method for tumor characterization.Approach.Two previously published MRI datasets with multiple measurements during and after radiotherapy, were used for development and testing:T2-weighted multi-echo images obtained for two mouse models of pancreatic cancer, and diffusion-weighted images for patients with brain metastases. Initially, the data was decomposed using the novel monotonous slope non-negative matrix factorization (msNMF) tailored for MR data. The following processing consisted of a tumor heterogeneity assessment using descriptive statistical measures, robust linear modelling to capture temporal changes of these, and finally logistic regression analysis for stratification of tumors and volumetric outcome.Main Results.The framework was able to classify the two pancreatic tumor types with an area under curve (AUC) of 0.999,P< 0.001 and predict the tumor volume change with a correlation coefficient of 0.513,P= 0.034. A classification of the human brain metastases into responders and non-responders resulted in an AUC of 0.74,P= 0.065.Significance.A general data processing framework for analyses of longitudinal MRI data has been developed and applications were demonstrated by classification of tumor type and prediction of radiotherapy response. Further, as part of the assessment, the merits of msNMF for tumor tissue decomposition were demonstrated.

Anterior cingulate glutamate levels associate with functional activation and connectivity during sensory integration in schizophrenia: a multimodal 1H-MRS and fMRI study.

BACKGROUND: Glutamatergic dysfunction has been implicated in sensory integration deficits in schizophrenia, yet how glutamatergic function contributes to behavioural impairments and neural activities of sensory integration remains unknown. METHODS: Fifty schizophrenia patients and 43 healthy controls completed behavioural assessments for sensory integration and underwent magnetic resonance spectroscopy (MRS) for measuring the anterior cingulate cortex (ACC) glutamate levels. The correlation between glutamate levels and behavioural sensory integration deficits was examined in each group. A subsample of 20 pairs of patients and controls further completed an audiovisual sensory integration functional magnetic resonance imaging (fMRI) task. Blood Oxygenation Level Dependent (BOLD) activation and task-dependent functional connectivity (FC) were assessed based on fMRI data. Full factorial analyses were performed to examine the Group-by-Glutamate Level interaction effects on fMRI measurements (group differences in correlation between glutamate levels and fMRI measurements) and the correlation between glutamate levels and fMRI measurements within each group. RESULTS: We found that schizophrenia patients exhibited impaired sensory integration which was positively correlated with ACC glutamate levels. Multimodal analyses showed significantly Group-by-Glutamate Level interaction effects on BOLD activation as well as task-dependent FC in a 'cortico-subcortical-cortical' network (including medial frontal gyrus, precuneus, ACC, middle cingulate gyrus, thalamus and caudate) with positive correlations in patients and negative in controls. CONCLUSIONS: Our findings indicate that ACC glutamate influences neural activities in a large-scale network during sensory integration, but the effects have opposite directionality between schizophrenia patients and healthy people. This implicates the crucial role of glutamatergic system in sensory integration processing in schizophrenia.

Effects of initiating insulin pump therapy in the real world: A nationwide, register-based study of adults with type 1 diabetes.

AIMS: We aimed to estimate effects of insulin pump therapy (IPT) on HbA1c level, HbA1c variability, and risk of hospitalised diabetic ketoacidosis (DKA) and severe hypoglycaemia (SH), compared with multiple daily insulin injections (MDI). METHODS: We identified a cohort of all adults with type 1 diabetes in Denmark using national registry data and assigned each individual to either IPT (treatment) or MDI (control) from 2010 to 2020. We estimated average treatment effects on the treated (ATT) and treatment effects among population subgroups using treatment-staggered difference-in-differences. RESULTS: The cohort consisted of 26,687 individuals with a collective 243,601 person-years of observation; 38,823 (16 %) were IPT person-years. We identified an ATT for HbA1c of -0.33 % (95 % CI -0.39 to -0.27; -3.6 mmol/mol [95 % CI -4.2 to -2.9]). ATTs were larger among women and individuals who were older, had highest baseline HbA1c, and used continuous glucose monitoring. ATT for HbA1c variability (-0.016 % [-0.028 to -0.0041); -0.17 mmol/mol [95 % CI -0.30 to -0.045]) corresponded to a 6.5 % decrease in the standard deviation of HbA1c. ATTs for DKA and SH corresponded to 0.52 additional and 0.11 fewer hospitalisations per 1,000 person-years, respectively. CONCLUSIONS: IPT significantly reduced HbA1c level and variability, compared with MDI. However, it also marginally increased the risk of hospitalised DKA.