Correlation between ambulatory function and clinical factors in hemiplegic patients with intact single lateral corticospinal tract: A pilot study

To define the relationship between the complete destruction of 1 lateral corticospinal tract (CST), as demonstrated by diffusion tensor imaging (DTI) tractography, and ambulatory function 6 months following stroke. Twenty-six adults (17 male, 9 female) with poststroke hemiplegia who were transferred to the physical medicine and rehabilitation department. Participants underwent DTI tractography, which showed that 1 lateral CST had been clearly destroyed. Functional ambulation classification (FAC) scores at admission, discharge, and 6 months after discharge were used to evaluate the patients’ ability to walk. The National Institutes of Health Stroke Scale (NIHSS) and the Korean version of the modified Barthel index (K-MBI) at admission, discharge, and 6 months after discharge were used to evaluate the degree of functional recovery. Of the 26 patients, 18 were nonambulatory (FAC level 1–3), and 8 were able to walk without support (FAC level 4–6). The type of stroke (infarction or hemorrhage), site of the lesion, spasticity of lower extremities, cranioplasty, and the time taken from onset to MRI were not statistically significantly correlated with the ability to walk. However, statistically significant correlations were found in relation to age, K-MBI scores, and initial NIHSS scores. Despite the complete damage to the lesion site and the preservation of 1 unilateral CST, as shown by DTI, good outcomes can be predicted on the basis of younger age, low NIHSS scores, and high MBI scores at onset

A Predictive Model with Data Scaling Methodologies for Forecasting Spare Parts Demand in Military Logistics

This study addresses the challenge of accurately forecasting demand for maintenance-related spare parts of the K-X tank, influenced by high uncertainty and external factors. Deep learning models with RobustScaler demonstrate significant improvements, achieving an accuracy of 86.90% compared to previous methods. RobustScaler outperforms other scaling models, enhancing machine learning performance across time series and data mining. By collecting eight years’ worth of demand data and utilising various consumption data items, this study develops accurate forecasting models that contribute to the advancement of spare parts demand forecasting. The results highlight the effectiveness of the proposed approach, showcasing its superiority in accuracy, precision, recall, and F1-Score. RobustScaler particularly excels in time series analysis, further emphasizing its potential for enhancing machine learning performance on diverse datasets. This study provides innovative techniques and insights, demonstrating the effectiveness of deep learning and data scaling methodologies in improving forecasting accuracy for maintenance spare parts demand

The Correlation between Climate Change and Corporate Performance

38-43The purpose of the study is to verify the correlation of the climate change risk focusing on the influence of carbon emission on the corporate performance and discriminative response of corporate contingent upon the publishment of Sustainability Report. The results of this study show that there is a negative (-) relationship between Carbon emission intensity and corporate performance. And the negative influence of carbon emission intensity on corporate performance was found to be smaller for companies that published sustainability reports than for those that did not. This study provided empirical evidences on why corporate’s active reactive activities according to the climate change is essential for sustainable development

Is poststroke complex regional pain syndrome the combination of shoulder pain and soft tissue injury of the wrist?: A prospective observational study STROBE of ultrasonographic findings in complex regional pain syndrome

Patients with poststroke complex regional pain syndrome (CRPS) show different symptoms compared to other types of CRPS, as they usually complain of shoulder and wrist pain with the elbow relatively spared. It is thus also known by the term “shoulder-hand syndrome.” The aim of this study is to present a possible pathophysiology of poststroke CRPS through ultrasonographic observation of the affected wrist before and after steroid injection at the extensor digitorum communis (EDC) tendon in patients suspected with poststroke CRPS. Prospective evaluation and observation, the STROBE guideline checklist was used. Twenty-three patients diagnosed as poststroke CRPS in accordance to clinical criteria were enrolled. They had a Three Phase Bone Scan (TPBS) done and the cross-sectional area (CSA) of EDC tendon was measured by using ultrasonography. They were then injected with steroid at the EDC tendon. The CSA of EDC tendon, visual analogue scale (VAS), and degree of swelling of the wrist were followed up 1 week after the injection. TPBS was interpreted as normal for 4 patients, suspected CRPS for 10 patients, and CRPS for 9 patients. Ultrasonographic findings of the affected wrist included swelling of the EDC tendon. After the injection of steroid to the wrist, CSA and swelling of the affected wrist compared to that before the treatment was significantly decreased (P < 0.001). The VAS score declined significantly after the injection (P < 0.001). Our results suggest that the pathophysiology of poststroke CRPS might be the combination of frozen shoulder or rotator cuff tear of shoulder and soft tissue injury of the wrist caused by the hemiplegic nature of patients with stroke

Combined Brown syndrome and superior oblique palsy without a trochlear nerve: case report

CCDD: congenital cranial dysinnervation disorder; MRI: magnetic resonance imaging; RHT: right hypertropia; SO: superior obliqueAbstract Background Congenital Brown syndrome is characterized by limited elevation particularly during adduction. The pathogenesis of congenital Brown syndrome is still controversial. Case presentation A 6-year-old boy had been tilting his head to the left since infancy. He showed right hypertropia (RHT) of 2 prism diopters (Δ) in the primary position. He showed RHT 6Δ in right gaze, RHT 2Δ in left gaze, RHT 12Δ in right head tilt, and orthotropia in left head tilt. The right eye showed limitation of elevation and depression on adduction, and the left eye showed overdepression on adduction. MR images showed an absent right trochlear nerve with a hypoplastic ipsilateral superior oblique muscle. Conclusions Congenital Brown syndrome may be associated with an absent trochlear nerve and hypoplastic superior oblique muscle suggesting an etiologic mechanism of congenital cranial dysinnervation disorder

Fluoroscopically Guided Balloon Dilation for Benign Anastomotic Stricture in the Upper Gastrointestinal Tract

A benign anastomotic stricture is a common complication of upper gastrointestinal (UGI) surgery and is difficult to manage conservatively. Fluoroscopically guided balloon dilation has a number of advantages and is a safe and effective procedure for the treatment of various benign anastomotic strictures in the UGI tract

Diagnosis and Prognosis Using Machine Learning Trained on Brain Morphometry and White Matter Connectomes

Accurate, reliable prediction of risk for Alzheimer’s disease (AD) is essential for early, diseasemodifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of commonly available multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping—morphometry and connectomics—and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (study 1: Ilsan Dementia Cohort; N=211; 110 AD, 64 mild cognitive impairment [MCI], and 37 subjective memory complaints [SMC]) to test and validate the diagnostic models; and, secondly, Alzheimer’s Disease Neuroimaging Initiative (ADNI)-2 (study 2) to test the generalizability of the approach and the prognostic models with longitudinal follow up data. Our machine learning models trained on the morphometric and connectome estimates (number of features=34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) with iterative nested cross-validation in a single-site study, outperforming the benchmark model (FLAIR-based white matter hyperintensity volumes). In a generalizability study using ADNI-2, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) as CSF biomarker model (t-tau, p-tau, and Amyloid β, and ratios). We also predicted MCI to AD progression with 69% accuracy, compared with the 70% accuracy using CSF biomarker model. The optimal classification accuracy in a single-site dataset and the reproduced results in multisite dataset show the feasibility of the high-throughput imaging analysis of multimodal MRI and data-driven machine learning for predictive modeling in AD