Increased Upper Extremity Muscle Mass in Ambulatory Children with Cerebral Palsy.

AIM: To compare muscle mass in the upper and lower extremities between ambulatory children with cerebral palsy (CP) and typically developing (TD) children. MATERIALS AND METHODS: A total of 21 children aged 2 to 12 years with CP and a Gross Motor Function Classification System (GMFCS) level of I, II, or III were matched with 21 TD children for age, sex, and body mass index. The lean body mass (LBM) of each extremity was calculated from whole-body dual-energy X-ray absorptiometry. RESULTS: The LBM of the upper extremities was greater in children with CP compared to TD children, and the difference was significant in the GMFCS level II group (1340.6 g vs. 1004.2 g, p = 0.027). There was no significant difference in the LBM of the lower extremities between the CP and TD groups (p = 0.190). The ratio of lower extremity LBM to total extremity LBM was lower in children with CP, while the ratio of upper extremity LBM to total extremity LBM was higher in children with CP (73.2% vs. 78.5% [p < 0.001] and 26.7% vs. 21.5% [p < 0.001], respectively). CONCLUSIONS: Ambulatory children with CP, especially in the GMFCS level II group, exhibit greater muscle mass in the upper extremities compared to TD children.

Syringomyelia: A New Phenotype of SPG11-Related Hereditary Spastic Paraplegia?

Hereditary spastic paraplegia (HSP) refers to a group of neurodegenerative disorders affecting motor neurons in the central nervous system. HSP type 11 is the most frequent subtype of autosomal recessive HSPs. Caused by pathogenic variants in SPG11, HSP type 11 has a heterogeneous clinical presentation, including various degrees of cognitive dysfunction, spasticity and weakness predominantly in the lower extremities among other features. An 8-year-old boy visited our rehabilitation clinic with a chief complaint of intellectual impairment. Motor weakness was not apparent, but he exhibited a mild limping gait with physical signs of upper motor neuron involvement. Next generation sequencing revealed biallelic pathogenic variants, c.2163dupT and c.5866+1G>A in SPG11, inherited biparentally which was confirmed by Sanger sequencing. Brain imaging study showed thinning of corpus callosum, consistent with previous reports, however whole spine imaging study revealed extensive syringomyelia in his spinal cord, a rare finding in HSP type 11. Further studies are needed to determine whether this finding is a true phenotype associated with HSP type 11.

Development of a machine learning-based clinical decision support system to predict clinical deterioration in patients visiting the emergency department.

This study aimed to develop a machine learning-based clinical decision support system for emergency departments based on the decision-making framework of physicians. We extracted 27 fixed and 93 observation features using data on vital signs, mental status, laboratory results, and electrocardiograms during emergency department stay. Outcomes included intubation, admission to the intensive care unit, inotrope or vasopressor administration, and in-hospital cardiac arrest. eXtreme gradient boosting algorithm was used to learn and predict each outcome. Specificity, sensitivity, precision, F1 score, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve were assessed. We analyzed 303,345 patients with 4,787,121 input data, resampled into 24,148,958 1 h-units. The models displayed a discriminative ability to predict outcomes (AUROC > 0.9), and the model with lagging 6 and leading 0 displayed the highest value. The AUROC curve of in-hospital cardiac arrest had the smallest change, with increased lagging for all outcomes. With inotropic use, intubation, and intensive care unit admission, the range of AUROC curve change with the leading 6 was the highest according to different amounts of previous information (lagging). In this study, a human-centered approach to emulate the clinical decision-making process of emergency physicians has been adopted to enhance the use of the system. Machine learning-based clinical decision support systems customized according to clinical situations can help improve the quality of care.

Case Report: The success of face analysis technology in extremely rare genetic diseases in Korea: Tatton-Brown-Rahman syndrome and Say-Barber -Biesecker-Young-Simpson variant of ohdo syndrome.

Tatton-Brown-Rahman syndrome (TBRS) and Say-Barber-Biesecker- Young-Simpson variant of Ohdo syndrome (SBBYSS) are extremely rare genetic disorders with less than 100 reported cases. Patients with these disorders exhibit a characteristic facial dysmorphism: TBRS is characterized by a round face, a straight and thick eyebrow, and prominent maxillary incisors, whereas SBBYSS is characterized by mask-like facies, blepharophimosis, and ptosis. The usefulness of Face2Gene as a tool for the identification of dysmorphology syndromes is discussed, because, in these patients, it suggested TBRS and SBBYSS within the top five candidate disorders. Face2Gene is useful for the diagnosis of extremely rare diseases in Korean patients, suggesting the possibility of expanding its clinical applications.

Mixture of quantum dots and ZnS nanoparticles as emissive layer for improved quantum dots light emitting diodes.

Recently, quantum dots based light-emitting diodes (QLEDs) have received huge attention due to the properties of quantum dots (QDs), such as high photoluminescence quantum yield (PLQY) and narrow emission. To improve the performance of QLEDs, reducing non-radiative energy transfer is critical. So far, most conventional methods required additional chemical treatment like giant shell and/or ligands exchange. However that triggers unsought shifted emission or reduced PLQY of QDs. In this work, we have firstly suggested a novel approach to improve the efficiency of QLEDs by introducing inorganic nanoparticles (NPs) spacer between QDs, without additional chemical treatment. As ZnS NPs formed a mixture layer with QDs, the energy transfer was reduced and the distance between the QDs increased, leading to improved PLQY of mixture layer. As a result, current efficiency (CE) of the QLED device was improved by twice compared with one using only QDs layer. This is an early report on utilizing ZnS NPs as an efficient spacer, which can be utilized to other compositions of QDs.

A feasible strategy to prepare quantum dot-incorporated carbon nanofibers as free-standing platforms.

Recently, quantum dots (QDs) have often garnered significant attention and have been employed for various applications. Nevertheless, most conventional devices utilize a glass substrate and/or brittle substrate, which is not compatible with next-generation wearable electronics. A suitable method for devising conductive and flexible free-standing platforms that can be combined with various kinds of QDs is thus in great need for next-generation wearable electronics. In this work, we introduce a universal and simple method to coat QDs on carbon nanofibers (CNFs) by a dip-coating process, where many kinds of QDs can be well decorated on the surface of CNFs. As one potential application among many, QD-coated CNFs were examined for their photocatalytic applications and characterization. As a result, it was found that the best performance of CdSe QD-coated CNFs for hydrogen production was 3.8 times higher than that of only QDs with the same 1 mg of QDs. This is an early report on fabricating various kinds of QD-coated CNFs, which can be extended to a myriad set of applications.