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We report the design, synthesis, photoswitching and computational studies of N-methyl arylazo-3,5-(di-2-pyridyl)pyrazole and its N-alkyl pyridinium derivatives with an ionic center proximally located to the azo group. Besides achieving excellent photoswitching characteristics, particularly at longer wavelengths, and tuning Z isomer stability due to the effects of counter ions and pH, the utility of neutral and ionic photoswitches for pH modulation by light was achieved.

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Neurovascular coupling (NVC) and neurometabolic coupling (NMC) provide the basis for functional magnetic resonance imaging and positron emission tomography to map brain neurophysiology. While increases in neuronal activity are often accompanied by increases in blood oxygen delivery and oxidative metabolism, these observations are not the rule. This decoupling is important when interpreting brain network organization (e.g., resting-state functional connectivity [RSFC]) because it is unclear whether changes in NMC/NVC affect RSFC measures. We leverage wide-field optical imaging in Thy1-jRGECO1a mice to map cortical calcium activity in pyramidal neurons, flavoprotein autofluorescence (representing oxidative metabolism), and hemodynamic activity during wake and ketamine/xylazine anesthesia. Spontaneous dynamics of all contrasts exhibit patterns consistent with RSFC. NMC/NVC relative to excitatory activity varies over the cortex. Ketamine/xylazine profoundly alters NVC but not NMC. Compared to awake RSFC, ketamine/xylazine affects metabolic-based connectomes moreso than hemodynamic-based measures of RSFC. Anesthesia-related differences in NMC/NVC timing do not appreciably alter RSFC structure.

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BACKGROUND: Whether optical computed tomography (OCT) and magnetic resonance imaging (MRI) findings are associated with final visual acuity in children with myelin oligodendrocyte glycoprotein antibody disease (MOGAD) optic neuritis is unclear. METHODS: We retrospectively reviewed the charts of pediatric patients with MOGAD optic neuritis seen at St. Louis Children's Hospital/Barnes Jewish Hospital since 2016. RESULTS: In the 12 patients in this study, presenting visual acuity was worse in the optic neuritis-affected eyes but significantly improved from presentation to follow-up, such that, at last follow-up, there was no longer a statistical difference between the affected and unaffected eyes. The number of affected eyes with nerve enhancement and the amount of optic nerve affected, as well as thickness of the retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), and macula, decreased from presentation to follow-up. Ultimately, none of these variables were associated with final visual acuity. CONCLUSION: In this cohort, pediatric MOGAD optic neuritis patients had positive visual outcomes despite significant RNFL thinning and involvement of the optic nerve on MRI, leading to a lack of correlation between follow-up visual acuity and OCT and MRI measures of disease severity, respectively.

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This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

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BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation free but previously has not been able to produce diagnostic-quality images of bone on a timeline suitable for clinical use. We developed automated motion correction and use deep learning to generate pseudo-CT images from MR images. We aim to evaluate whether motion-corrected pseudo-CT produces cranial images that have potential to be acceptable for clinical use. MATERIALS AND METHODS: Patients younger than age 18 who underwent CT imaging of the head for either trauma or evaluation of cranial suture patency were recruited. Subjects underwent a 5-minute golden-angle stack-of-stars radial volumetric interpolated breath-hold MR image. Motion correction was applied to the MR imaging followed by a deep learning-based method to generate pseudo-CT images. CT and pseudo-CT images were evaluated and, based on indication for imaging, either presence of skull fracture or cranial suture patency was first recorded while viewing the MR imaging-based pseudo-CT and then recorded while viewing the clinical CT. RESULTS: A total of 12 patients underwent CT and MR imaging to evaluate suture patency, and 60 patients underwent CT and MR imaging for evaluation of head trauma. For cranial suture patency, pseudo-CT had 100% specificity and 100% sensitivity for the identification of suture closure. For identification of skull fractures, pseudo-CT had 100% specificity and 90% sensitivity. CONCLUSIONS: Our early results show that automated motion-corrected and deep learning-generated pseudo-CT images of the pediatric skull have potential for clinical use and offer a high level of diagnostic accuracy when compared with standard CT scans.

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Endometrial cancer is the fourth most common cancer in women in the United States, with a lifetime risk of approximately 2.8%. Precise histologic evaluation and molecular classification of endometrial cancer are important for effective patient management and determining the best treatment options. This study introduces EndoNet, which uses convolutional neural networks for extracting histologic features and a vision transformer for aggregating these features and classifying slides into high- and low-grade cases. The model was trained on 929 digitized hematoxylin and eosin-stained whole-slide images of endometrial cancer from hysterectomy cases at Dartmouth-Health. It classifies these slides into low-grade (endometrioid grades 1 and 2) and high-grade (endometrioid carcinoma International Federation of Gynecology and Obstetrics grade 3, uterine serous carcinoma, or carcinosarcoma) categories. EndoNet was evaluated on an internal test set of 110 patients and an external test set of 100 patients from The Cancer Genome Atlas database. The model achieved a weighted average F1 score of 0.91 (95% CI, 0.86 to 0.95) and an area under the curve of 0.95 (95% CI, 0.89 to 0.99) on the internal test, and 0.86 (95% CI, 0.80 to 0.94) for F1 score and 0.86 (95% CI, 0.75 to 0.93) for area under the curve on the external test. Pending further validation, EndoNet has the potential to support pathologists without the need of manual annotations in classifying the grades of gynecologic pathology tumors.

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The authors have developed a paradigm using positron emission tomography (PET) with multiple radiopharmaceutical tracers that combines measurements of cerebral metabolic rate of glucose (CMRGlc), cerebral metabolic rate of oxygen (CMRO2), cerebral blood flow (CBF), and cerebral blood volume (CBV), culminating in estimates of brain aerobic glycolysis (AG). These in vivo estimates of oxidative and non-oxidative glucose metabolism are pertinent to the study of the human brain in health and disease. The latest positron emission tomography-computed tomography (PET-CT) scanners provide time-of-flight (TOF) imaging and critical improvements in spatial resolution and reduction of artifacts. This has led to significantly improved imaging with lower radiotracer doses. Optimized methods for the latest PET-CT scanners involve administering a sequence of inhaled 15O-labeled carbon monoxide (CO) and oxygen (O2), intravenous 15O-labeled water (H2O), and 18F-deoxyglucose (FDG)-all within 2-h or 3-h scan sessions that yield high-resolution, quantitative measurements of CMRGlc, CMRO2, CBF, CBV, and AG. This methods paper describes practical aspects of scanning designed for quantifying brain metabolism with tracer kinetic models and arterial blood samples and provides examples of imaging measurements of human brain metabolism.

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Trunk muscles maintain steady effort with adequate strength and endurance. When the muscle performance is subpar, it might cause lower back discomfort. No reference for trunk strength and endurance has been established previously. The aim of this study was to determine the normative reference values for dynamometric and non-dynamometric tests in people with various body fat percentages. Two hundred sixty-four participants aged 19-40 years old were recruited in this cross-sectional study. The Siri equation was used to calculate the individuals body fat proportions, which were divided into normal, high, and very high body fat for men and women. The Modified Sorenson's and the Back-Leg-Chest Dynamometric tests were utilized to measure muscular performance. The means of strength in females with normal, high, and very high body fat percentages were 27.39, 25.75, and 25.37 N/m2, respectively. The males in the same category had the means of 56.48, 51.79, and 60.17 N/m2, respectively. The highest mean of endurance in females was in those with normal body fat percentage (42.28), so did males (71.02). Our findings suggest that males had higher trunk muscle strength and endurance than females, and normal-body-fat individuals had the greatest endurance regardless of gender.

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OBJECTIVE: The objective of the study was to evaluate the efficacy of Maitland accessory mobilization and neural mobilization in patients with tennis elbow. METHOD: Twenty-five patients meeting the selection criteria were randomly assigned to three experimental groups: Group C (conventional treatment), Group B (neural mobilization), and Group A (Maitland mobilization). Quality of life was assessed using the Patient Rated Tennis Elbow Evaluation (PRTEE), while pain, range of motion, and grip strength were evaluated using the Visual Analog Scale (VAS), a universal goniometer, and a handheld dynamometer. The interventions were administered three times per week for four weeks to the respective groups. RESULTS: Non-parametric tests were employed to analyze the results due to the non-normal distribution of the data (p < 0.05). Both the Wilcoxon signed-rank test and the Kruskal-Wallis test were utilized to assess differences within and between groups. The results of the between-group analysis demonstrated significant differences in pain (p = 0.018) and quality of life (p = 0.045) among the three groups. CONCLUSION: After a 4-week intervention, all three groups exhibited notable improvements in discomfort levels, grip strength, and quality of life. Notably, Group B demonstrated the most substantial increase in range of motion (ROM) compared to Groups A and C. Consequently, incorporating neural mobilization into the treatment plan is recommended for patients experiencing Tennis Elbow.

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Brain glucose metabolism, which can be investigated at the macroscale level with [18F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown. Here, using two multimodal datasets of healthy participants, we built a multivariable multilevel model of functional-metabolic associations, assessing multiple functional features, describing the 1) rs-fMRI signal, 2) hemodynamic response, 3) static and 4) time-varying functional connectivity, as predictors of the human brain's metabolic architecture. The full model was trained on one dataset and tested on the other to assess its reproducibility. We found that functional-metabolic spatial coupling is nonlinear and heterogeneous across the brain, and that local measures of rs-fMRI activity and synchrony are more tightly coupled to local metabolism. In the testing dataset, the degree of functional-metabolic spatial coupling was also related to peripheral metabolism. Overall, although a significant proportion of regional metabolic variability can be described by measures of spontaneous activity, additional efforts are needed to explain the remaining variance in the brain's 'dark energy'.

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BACKGROUND AND PURPOSE: Children with cerebral malaria have an elevated risk of mortality and neurologic morbidity. Both mortality and morbidity are associated with initially increased brain volume on MR imaging, as graded by the Brain Volume Score, a subjective ordinal rating scale created specifically for brain MRIs in children with cerebral malaria. For the Brain Volume Score to be more widely clinically useful, we aimed to determine its independent reproducibility and whether it can be applicable to lower-resolution MRIs. MATERIALS AND METHODS: To assess the independent reproducibility of the Brain Volume Score, radiologists not associated with the initial study were trained to score MRIs from a new cohort of patients with cerebral malaria. These scores were then compared with survival and neurologic outcomes. To assess the applicability to lower-resolution MRI, we assigned Brain Volume Scores to brain MRIs degraded to simulate a very-low-field (64 mT) portable scanner and compared these with the original scores assigned to the original nondegraded MRIs. RESULTS: Brain Volume Scores on the new cohort of patients with cerebral malaria were highly associated with outcomes (OR for mortality = 16, P < .001). Scoring of the simulated degraded images remained consistent with the Brain Volume Scores assigned to the original higher-quality (0.35 T) images (intraclass coefficients > 0.86). CONCLUSIONS: Our findings demonstrate that the Brain Volume Score is externally valid in reproducibly predicting outcomes and can be reliably assigned to lower-resolution images.

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BACKGROUND: Lateral Ankle Sprain (LAS) is a recurrent musculoskeletal injury commonly noticed in primary care, podiatry, orthopaedics, and physical therapy centers. The Foot and Ankle Disability Index (FADI) is a self-reported and region-specific tool with no previous literature available on the translation of the FADI scale into Hindi language. AIM: The study aims to translate and evaluate each translated domain of FADI to see its cross-cultural adaptation, content validity and reliability for patients with chronic recurrent LAS. STUDY DESIGN: A Cross-Sectional Study. METHODS: The scale was translated from the reference language to the target language, Hindi, using the instructions provided in the literature. Delphi survey was conducted for content validation followed by recruitment of 51 participants with a history of long lasting repetitive lateral sprain of ankle to evaluate test-retest reliability of Hindi version of FADI. RESULT: The S-CVI/Ave and S-CVI/UA came out to be 0.988 and 0.884, respectively and I-CVI for all items of Hindi version of FADI were more than 0.90. The ICC (Intra-class Correlation Coefficient) and internal consistency was evaluated, which came out to 0.961 and 0.980, respectively for Hindi version of FADI. CONCLUSION: Hindi version of FADI is a valid and reliable scale that has been translated and adapted to be implemented among Indian population suffering from long lasting repetitive LAS.

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White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the established relationship between WMH burden and age. We found that TrUE-Net was highly reliable at identifying WMH regions with low false positive rates, when compared to semi-manual segmentation as the reference standard. TrUE-Net performed similarly or favorably when compared to the other automated techniques. Moreover, TrUE-Net was able to detect relationships between WMH and age to a similar degree as the reference standard semi-manual segmentation at both the global and regional level. These results support the use of TrUE-Net for identifying WMH at the global or regional level, including in large, combined datasets.

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Purpose: To develop and validate a semisupervised style transfer-assisted deep learning method for automated segmentation of the kidneys using multiphase contrast-enhanced (MCE) MRI acquisitions. Materials and Methods: This retrospective, Health Insurance Portability and Accountability Act-compliant, institutional review board-approved study included 125 patients (mean age, 57.3 years; 67 male, 58 female) with renal masses. Cohort 1 consisted of 102 coronal T2-weighted MRI acquisitions and 27 MCE MRI acquisitions during the corticomedullary phase. Cohort 2 comprised 92 MCE MRI acquisitions (23 acquisitions during four phases each, including precontrast, corticomedullary, early nephrographic, and nephrographic phases). The kidneys were manually segmented on T2-weighted images. A cycle-consistent generative adversarial network (CycleGAN) was trained to generate anatomically coregistered synthetic corticomedullary style images using T2-weighted images as input. Synthetic images for precontrast, early nephrographic, and nephrographic phases were then generated using the synthetic corticomedullary images as input. Mask region-based convolutional neural networks were trained on the four synthetic phase series for kidney segmentation using T2-weighted masks. Segmentation performance was evaluated in a different cohort of 20 originally acquired MCE MRI examinations by using Dice and Jaccard scores. Results: The CycleGAN network successfully generated anatomically coregistered synthetic MCE MRI-like datasets from T2-weighted acquisitions. The proposed deep learning approach for kidney segmentation achieved high mean Dice scores in all four phases of the original MCE MRI acquisitions (0.91 for precontrast, 0.92 for corticomedullary, 0.91 for early nephrographic, and 0.93 for nephrographic). Conclusion: The proposed deep learning approach achieved high performance in kidney segmentation on different MCE MRI acquisitions.Keywords: Kidney Segmentation, Generative Adversarial Network, CycleGAN, Convolutional Neural Network, Transfer Learning Supplemental material is available for this article. Published under a CC BY 4.0 license.

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BACKGROUND: In advanced-stage epithelial ovarian cancer (EOC) standard of care is upfront debulking surgery (UDS) followed by adjuvant chemotherapy. Interval debulking surgery after neoadjuvant chemotherapy(NACT-IDS) is a reasonable alternative. METHODS: This study was a retrospective review of patients of Stage III/IV EOC treated either by UDS or NACT-IDS between January 2016 and December 2018 to report the comparison of progression-free survival(PFS) and overall survival(OS) of patients with advanced-stage EOC treated with either UDS or NACT-IDS. RESULTS: Out of 50 patients, 19 (38%) underwent UDS, and 31 (62%) received NACT. The mean follow-up duration was 27.7 months. No gross residual disease was achieved in 52.6% of the UDS group and in 70.4% of the NACT-IDS group. The median PFS of 20 and 30 months was observed in the UDS and NACT-IDS groups, respectively (log-rank P = 0.054). The median OS was 36 months in the NACT-IDS group and could not be reached in the UDS group (log-rank P = 0.329). Only residual disease was significantly associated with survival (hazards ratio 3.03, 95% confidence interval: 1.19-7.74) on multivariate Cox regression analysis. CONCLUSIONS: In advanced-stage EOC, the survival outcomes of NACT-IDS are comparable with those of UDS. Apart from the patient-specific parameters, the decision for UDS or NACT-IDS should take in account the expertise of the surgeon and the institutional capacity as a whole.

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Background: The management of diabetic peripheral neuropathy (DPN) comprises a multidimensional approach. Along with pharmacological treatment, physiotherapy has gained applaudable popularity in improving the symptoms of DPN. Neuromuscular taping (NMT) is effective in improving motor, sensory, and balance impairments in many neuromuscular and musculoskeletal conditions but no research has conducted to evaluate the effect of NMT on balance, proprioception, pain, and nerve conduction parameters in patients with DPN. Purpose: To evaluate the effectiveness of NMT on balance, proprioception, pain, and nerve conduction parameters in patients with DPN. Methods: 50 DPN patients aged 40-60 years, scored ≥ 2/13 on physical appearance and ≥ 1/10 on physical examination of Michigan Neuropathy Screening Instrument (MNSI), > 12 on Leeds Assessment of Neuropathic Symptom and Sign (LANSS) scale and < 45 on Berg Balance Scale (BBS) will be included. The experimental group (EG) will receive NMT at the tibialis anterior, tibialis posterior, and peroneus longus muscle and transverse arch of the foot and TENS at the tibial and peroneal nerves (80 Hz, 50 Amp, 0.2 ms square pulses, 2 to 3 times sensory threshold) and the control group (CG) will receive sham taping at the ankle joint and TENS with the same parameters as EG. Outcome measures will be taken at baseline, at 4 weeks, and at 8 weeks of intervention, respectively. Conclusion: The results obtained upon completion of this study may provide a cost-effective non-invasive treatment option to improve the outcomes that will be measured in the present study in patients with DPN. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01275-5.

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The authors review the phenomenon of third ventricular dilation causing chiasmal compression and vision loss, emphasize the need for further study given continued poor outcomes, and, in a patient case, illustrate the value of obtaining magnetic resonance imaging and nerve and macular optical coherence tomography in a patient with an unclear mechanism of vision loss. [J Pediatr Ophthalmol Strabismus. 2023;60(5):e49-e54.].

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INTRODUCTION: Vascular damage in Alzheimer's disease (AD) has shown conflicting findings particularly when analyzing longitudinal data. We introduce white matter hyperintensity (WMH) longitudinal morphometric analysis (WLMA) that quantifies WMH expansion as the distance from lesion voxels to a region of interest boundary. METHODS: WMH segmentation maps were derived from 270 longitudinal fluid-attenuated inversion recovery (FLAIR) ADNI images. WLMA was performed on five data-driven WMH patterns with distinct spatial distributions. Amyloid accumulation was evaluated with WMH expansion across the five WMH patterns. RESULTS: The preclinical group had significantly greater expansion in the posterior ventricular WM compared to controls. Amyloid significantly associated with frontal WMH expansion primarily within AD individuals. WLMA outperformed WMH volume changes for classifying AD from controls primarily in periventricular and posterior WMH. DISCUSSION: These data support the concept that localized WMH expansion continues to proliferate with amyloid accumulation throughout the entirety of the disease in distinct spatial locations.

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