BACKGROUND AND OBJECTIVES

Orthodontic tooth movement is driven by bone remodeling influenced by systemic factors, including caffeine and ethanol. This study aimed to investigate the effects of caffeine and ethanol on the expression of Receptor Activator of Nuclear Factor κβ (RANK) and Osteoprotegerin (OPG), key bone remodeling biomarkers, during orthodontic tooth movement.

METHODS

A laboratory experimental study was conducted on 30 male Wistar rats divided into three groups: K1 (orthodontic force only), K2 (force + caffeine), and K3 (force + ethanol). Orthodontic force was applied using Ni-Ti coil springs. Caffeine and ethanol were administered orally daily. On days 7 and 14, maxillary tissues were collected and analyzed via immunohistochemistry for RANK and OPG expression. Data were analyzed using One-Way ANOVA and Independent Sample T-tests with significance at pRESULTS

Caffeine and ethanol administration increased RANK and OPG expression compared to controls; however, only the ethanol group showed a significant increase in RANK expression on day 14 (p = 0.044). OPG expression was significantly higher in treatment groups at both time points (pCONCLUSION

Caffeine and ethanol modulate bone remodeling marker expression during orthodontic force application, with ethanol significantly increasing RANK expression at later stages. Further studies are needed to clarify the clinical implications for orthodontic treatment.

Animals ; Tooth Movement Techniques ; Tooth Movement ; Osteoprotegerin ; Role ; Movement ; Ethanol ; Bone Remodeling ; Caffeine ; Immunohistochemistry

BACKGROUND

 Neuromuscular and movement disorders comprise a heterogeneous group of acquired and inherited conditions affecting the motor unit and central movement pathways. Genetic data from underserved populations, including Filipinos, remain limited, highlighting the need for population-specific characterization.

OBJECTIVE

To characterize inherited neuromuscular and movement disorders among Filipinos and determine the diagnostic yield and genetic spectrum using next-generation sequencing (NGS).

METHODS

This referral single-center retrospective study reviewed Filipino patients who underwent genetic testing for suspected inherited neuromuscular and movement disorders. Variants were classified according to the American College of Medical Genetics and Genomics (ACMG) criteria.

RESULTS

Among 85 patients, 24 (28.2%) had pathogenic/likely pathogenic variants, 33 (38.8%) had variants of uncertain significance (VUS) and 28 (32.9%) were negative. Confirmed diagnoses included pediatric cases of limb-girdle muscular dystrophy, Duchenne muscular dystrophy, spinal muscular atrophy and GNE-related myopathy, and adult cases with myofibrillar myopathy, spinocerebellar ataxia and amyotrophic lateral sclerosis. Pathogenic variants involved 26 genes, most commonly SMN1.

CONCLUSION

This NGS-based characterization of inherited neuromuscular and movement disorders in Filipinos showed 28% diagnostic yield and a spectrum comparable to other Asian cohorts. The high rate of VUS underscores the need for family segregation studies and careful genotype–phenotype correlation. This study highlights the critical role of genetic testing in accurate diagnosis and targeted management to improve outcomes for patients with these rare disorders.

Retrospective Studies ; Referral And Consultation ; Population ; Movement Disorders ; Movement

A 19-year-old female with a 2-day history of involuntary fast jerk-like movements of the left upper and lower extremities presented at the emergency department. Patient had no other known comorbidities and family history was unremarkable. Anti-streptolysin O titer (ASO) and C-reactive protein (CRP) were all normal. Two-dimensional echocardiography (2D Echo) revealed thickened anterior mitral valve leaflet with prolapsed A2 scallop, mild mitral regurgitation, thickened right coronary cusp of aortic valve without restriction of motion, trivial aortic regurgitation, other findings were unremarkable. Patient was managed as a case of Sydenham’s chorea secondary to acute rheumatic fever, with valvular heart disease secondary. Patient was initially started on valproic acid 500mg tablet every 8 hours, benzathine penicillin 1.2M units intramuscular, and carvedilol 12.5mg/tablet twice a day. The patient was then shifted to haloperidol 5mg ¼ tablet twice a day, diphenhydramine 50mg intravenously coinciding with haloperidol doses due to visual side effects of valproic acid. This report highlights the importance of a high index of suspicion and complete history and physical examination in order to diagnose and manage movement disorders in a low-income setting.

Human ; Female ; Young Adult: 19-24 Yrs Old ; Movement Disorders ; Diphenhydramine ; Aortic Valve Insufficiency ; Heart Valve Diseases ; C-reactive Protein

BACKGROUND AND OBJECTIVES

Orthodontic tooth movement is driven by bone remodeling influenced by systemic factors, including caffeine and ethanol. This study aimed to investigate the effects of caffeine and ethanol on the expression of Receptor Activator of Nuclear Factor κβ (RANK) and Osteoprotegerin (OPG), key bone remodeling biomarkers, during orthodontic tooth movement.

METHODS

A laboratory experimental study was conducted on 30 male Wistar rats divided into three groups: K1 (orthodontic force only), K2 (force + caffeine), and K3 (force + ethanol). Orthodontic force was applied using Ni-Ti coil springs. Caffeine and ethanol were administered orally daily. On days 7 and 14, maxillary tissues were collected and analyzed via immunohistochemistry for RANK and OPG expression. Data were analyzed using One-Way ANOVA and Independent Sample T-tests with significance at pRESULTS

Caffeine and ethanol administration increased RANK and OPG expression compared to controls; however, only the ethanol group showed a significant increase in RANK expression on day 14 (p = 0.044). OPG expression was significantly higher in treatment groups at both time points (pCONCLUSION

Caffeine and ethanol modulate bone remodeling marker expression during orthodontic force application, with ethanol significantly increasing RANK expression at later stages. Further studies are needed to clarify the clinical implications for orthodontic treatment.

Animals ; Tooth Movement Techniques ; Tooth Movement ; Osteoprotegerin ; Role ; Movement ; Ethanol ; Bone Remodeling ; Caffeine ; Immunohistochemistry

Ginsenoside Rg_2(GRg2) is a triterpenoid compound found in Panax notoginseng. This study explored its effects and mechanisms on diabetic retinopathy and angiogenesis. The study employed endothelial cell models induced by glucose or vascular endothelial growth factor(VEGF), the chorioallantoic membrane(CAM) model, the oxygen-induced retinopathy(OIR) mouse model, and the db/db mouse model to evaluate the therapeutic effects of GRg2 on diabetic retinopathy and angiogenesis. Transwell assays and endothelial tube formation experiments were conducted to assess cell migration and tube formation, while vascular area measurements were applied to detect angiogenesis. The impact of GRg2 on the retinal structure and function of db/db mice was evaluated through retinal thickness and electroretinogram(ERG) analyses. The study investigated the mechanisms of GRg2 by analyzing the activation of Yes-associated protein(YAP) and Toll-like receptors(TLRs) pathways. The results indicated that GRg2 significantly reduced cell migration numbers and tube formation lengths in vitro. In the CAM model, GRg2 exhibited a dose-dependent decrease in the vascular area ratio. In the OIR model, GRg2 notably decreased the avascular and neovascular areas, ameliorating retinal structural disarray. In the db/db mouse model, GRg2 increased the total retinal thickness and enhanced the amplitudes of the a-wave, b-wave, and oscillatory potentials(OPs) in the ERG, improving retinal structural disarray. Transcriptomic analysis revealed that the TLR signaling pathway was significantly down-regulated following YAP knockdown, with PCR results consistent with the transcriptome sequencing findings. Concurrently, GRg2 downregulated the expression of Toll-like receptor 4(TLR4), TNF receptor-associated factor 6(TRAF6), and nuclear factor-kappaB(NF-κB) proteins in high-glucose-induced endothelial cells. Collectively, GRg2 inhibits cell migration and tube formation and significantly reduces angiogenesis in CAM and OIR models, improving retinal structure and function in db/db mice, with its pharmacological mechanism likely involving the down-regulation of YAP expression.
Animals ; Ginsenosides/pharmacology* ; Diabetic Retinopathy/physiopathology* ; Mice ; YAP-Signaling Proteins ; Humans ; Male ; Signal Transduction/drug effects* ; Cell Movement/drug effects* ; Adaptor Proteins, Signal Transducing/genetics* ; Mice, Inbred C57BL ; Neovascularization, Pathologic/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Panax notoginseng/chemistry* ; Endothelial Cells/metabolism* ; Transcription Factors/genetics* ; Angiogenesis

The zebrafish model has attracted much attention due to its strong reproductive ability, short research cycle, and ease of maintenance. It has always been an important vertebrate model system, often used to carry out human disease research. Its motor behavior features have the advantages of being simpler, more intuitive, and quantifiable. In recent years, it has received widespread attention in the study of traditional Chinese medicine(TCM)for the treatment of sleep disorders, neurodegenerative diseases, fatigue, epilepsy, and other diseases. This paper reviews the characteristics of zebrafish motor behavior and its applications in the pharmacodynamic verification and mechanism research of TCM extracts, active ingredients, and TCM compounds, as well as in active ingredient screening and safety evaluation. The paper also analyzes its advantages and disadvantages, with the aim of improving the breadth and depth of zebrafish and its motor behavior applications in the field of TCM research.
Zebrafish/physiology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Disease Models, Animal ; Drug Evaluation, Preclinical/methods* ; Animals ; Sleep Wake Disorders/physiopathology* ; Epilepsy/physiopathology* ; Neurodegenerative Diseases/physiopathology* ; Fatigue/physiopathology* ; Behavior, Animal/physiology* ; Motor Activity/physiology*

Motor imagery (MI) is a mental process that can be recognized by electroencephalography (EEG) without actual movement. It has significant research value and application potential in the field of brain-computer interface (BCI) technology. To address the challenges posed by the non-stationary nature and low signal-to-noise ratio of MI-EEG signals, this study proposed a Riemannian spatial filtering and domain adaptation (RSFDA) method for improving the accuracy and efficiency of cross-session MI-BCI classification tasks. The approach addressed the issue of inconsistent data distribution between source and target domains through a multi-module collaborative framework, which enhanced the generalization capability of cross-session MI-EEG classification models. Comparative experiments were conducted on three public datasets to evaluate RSFDA against eight existing methods in terms of classification accuracy and computational efficiency. The experimental results demonstrated that RSFDA achieved an average classification accuracy of 79.37%, outperforming the state-of-the-art deep learning method Tensor-CSPNet (76.46%) by 2.91% ( P < 0.01). Furthermore, the proposed method showed significantly lower computational costs, requiring only approximately 3 minutes of average training time compared to Tensor-CSPNet's 25 minutes, representing a reduction of 22 minutes. These findings indicate that the RSFDA method demonstrates superior performance in cross-session MI-EEG classification tasks by effectively balancing accuracy and efficiency. However, its applicability in complex transfer learning scenarios remains to be further investigated.
Electroencephalography/methods* ; Brain-Computer Interfaces ; Humans ; Imagination/physiology* ; Signal Processing, Computer-Assisted ; Movement/physiology* ; Signal-To-Noise Ratio ; Deep Learning ; Algorithms

Clinical grading diagnosis of disorder of consciousness (DOC) patients relies on behavioral assessment, which has certain limitations. Combining multi-modal technologies and brain-computer interface (BCI) paradigms can assist in identifying patients with minimally conscious state (MCS) and vegetative state (VS). This study collected electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals under motor BCI paradigms from 14 DOC patients, who were divided into two groups based on clinical scores: 7 in the MCS group and 7 in the VS group. We calculated event-related desynchronization (ERD) and motor decoding accuracy to analyze the effectiveness of motor BCI paradigms in detecting consciousness states. The results showed that the classification accuracies for left-hand and right-hand movement tasks using EEG were 93.28% and 76.19% for the MCS and VS groups, respectively; the classification precisions using fNIRS were 53.72% and 49.11% for these groups. When combining EEG and fNIRS features, the classification accuracies for left-hand and right-hand movement tasks in the MCS and VS groups were 95.56% and 87.38%, respectively. Although there was no statistically significant difference in motor decoding accuracy between the two groups, significant differences in ERD were observed between different consciousness states during left-hand movement tasks ( P < 0.001). This study demonstrates that motor BCI paradigms can assist in assessing the level of consciousness, with EEG being more sensitive for evaluating residual motor intention intensity. Moreover, the ERD feature of motor intention intensity is more sensitive than BCI classification accuracy.
Humans ; Brain-Computer Interfaces ; Spectroscopy, Near-Infrared/methods* ; Electroencephalography/methods* ; Consciousness Disorders/diagnosis* ; Male ; Movement ; Adult ; Female ; Intention ; Persistent Vegetative State/diagnosis*

In order to investigate the mechanical response of lumbar vertebrae during gait cycle in adolescents with idiopathic scoliosis (AIS), the present study was based on computed tomography (CT) data of AIS patients to construct model of the left support phase (ML) and model of the right support phase (MR), respectively. Firstly, material properties, boundary conditions and load loading were set to simulate the lumbar vertebra-pelvis model. Then, the difference of stress and displacement in the lumbar spine between ML and MR was compared based on the stress and displacement cloud map. The results showed that in ML, the lumbar stress was mostly distributed on the convex side, while in MR, it was mostly distributed on the concave side. The stress of the two types of stress mainly gathered near the vertebral arch plate, and the stress of the vertebral arch plate was transmitted to the vertebral body through the pedicle with the progress of gait. The average stress of the intervertebral tissue in MR was greater than that in ML, and the difference of stress on the convex and convex side was greater. The displacement of lumbar vertebrae in ML decreased gradually from L1 to L5. The opposite is true in MR. In conclusion, this study can accurately quantify the stress on the lumbar spine during gait, and may provide guidance for brace design and clinical decision making.
Humans ; Lumbar Vertebrae/diagnostic imaging* ; Scoliosis/diagnostic imaging* ; Adolescent ; Gait/physiology* ; Biomechanical Phenomena ; Tomography, X-Ray Computed ; Stress, Mechanical ; Female ; Male

In order to accurately capture the respiratory muscle movement and extract the synchronization signals corresponding to the breathing phases, a comprehensive signal sensing system for sensing the movement of the respiratory muscle was developed with applying the thin-film varistor FSR402 IMS-C07A in this paper. The system integrated a sensor, a signal processing circuit, and an application program to collect, amplify and denoise electronic signals. Based on the respiratory muscle movement sensor and a STM32F107 development board, an experimental platform was designed to conduct experiments. The respiratory muscle movement data and respiratory airflow data were collected from 3 healthy adults for comparative analysis. In this paper, the results demonstrated that the method for determining respiratory phase based on the sensing the respiratory muscle movement exhibited strong real-time performance. Compared to traditional airflow-based respiratory phase detection, the proposed method showed a lead times ranging from 33 to 210 ms [(88.3 ± 47.9) ms] for expiration switched into inspiration and 17 to 222 ms [(92.9 ± 63.8) ms] for inspiration switched into expiration, respectively. When this system is applied to trigger the output of the ventilator, it will effectively improve the patient-ventilator synchrony and facilitate the ventilation treatment for patients with respiratory diseases.
Humans ; Respiratory Muscles/physiology* ; Signal Processing, Computer-Assisted ; Movement/physiology* ; Respiration ; Monitoring, Physiologic/methods* ; Adult