Objective To summarize the clinical characteristics of myotonic dystrophy(DM).Methods The clinical data of 24 DM cases were analyzed retrospectively.Results 83.3%(20/24) of the patients obtained the disease during youth and it progressed slowly.79.2%(19/24) of the patients had positive family history.DM was a multisystem disease characterizing by myotonia,weakness and atrophy involved in multiple muscle groups,especially in distal limbs,neck and face.Extensors were more severe than flexors.Spontaneous myotonic discharges and myogenic damages were shown on electromyogram.Pathological examination of muscle biopsies showed increased number of central nuclei,nuclear chains and predominant atrophic typeⅠfibers in 8 cases,muscle fiber necrosis in 7 cases,fibrous structure disorder in 4 cases,sarcoplasmic masses in 3 cases,and serration of sarolemma in 2 cases.Conclusions The clinical characteristics of DM are weakness,atrophy and myotonia.Electromyogram and muscle biopsy are helpful in diagnosis of this disease.

Objective To investigate the clinical features of patients with multiple sclerosis (MS) and restless legs syndrome (RLS) and to further examine relevant factors that may contribute to the co-occurrence of MS and RLS.Methods Seventy MS patients were recruited in the present study.The RLS screen was further performed in MS patients based on the diagnostic criteria for RLS.MS patients with RLS were designated as the case group and MS patients without RLS served as the control group.The clinical data including age of MS onset,MS duration and clinical disability by the expanded disability status scale (EDSS) were analyzed.Results There were 12 MS patients with RLS in total 70 MS patients and the incidence rate was 17.1％.The average age of MS onset in the RLS group was (47.6 ± 10.0) years,and (40.1 ± 10.4 ) years in the control group.The difference of average age of MS onset was found to be significant (t =2.29,P =0.030).The average history of MS in the RLS group was ( 12.6 ± 6.8 ) years,and ( 8.2 ± 6.6) years in the control group ( t =2.10,P =0.039).The average EDSS of the RLS group was 4.5 ±2.5,and 2.5 ±2.0 in the control group (t =3.02,P =0.004).There was no significant association between RLSRS and EDSS in MS patients with RLS (P =0.15).Conclusion The incidence rate of RLS in MS patients was high.Among patients with MS,RLS was associated with older age,longer MS duration,and more severe disability.

Objective To investigate the photochemotherapeutic effect and the main affecting factors of PSD-007 on human cervical cancer Hela in vitro.Methods Hela cells were treated with different concentrations of PSD-007 (0,3.125,6.25,12.5,25,50,100 μg/ml) for 2 h under the influence of low-level laser (635 nm) therapy at different doses (0,0.6,1.2,2.4,4.8,9.6 J/cm2).Then the OD values and survival rates of Hela cells were measured by MTT assay compared with breast cancer cells MCF-7 in same treatment.Hela cells were treated with 12.5 μg/ml of PSD-007 for 2 h and were treated with different intensities of laser (1.2,2.4,4.8 J/cm2).The cellular apoptosis rate and cell cycle phase distribution of Hela were measured by a flow cytometry (FCM).Results Survival rates of Hela cells declined with more than 25 μg/ml of PSD-007 only,and significant difference in the inhibitory between the PDT group and control group was observed (P＜0.05).The survival rates of Hela after PDT was decreased by the concentration of sensitizer and dose of laser.There were no significant differences of cell survival rates among the groups with concentrations more than 12.5 μg/ml and laser energy density more than 4.8 J/cm2.The FCM assay showed a G0/G1 cell cycle arrest in a time-dependent manner.Conclusions PSD-007 has a photodynamic effect on Hela in vitro.Photodynamic effect of PSD-007 was more significant in Hela than MCF-7.Less photosensitizer and laser energy density were needed.

Exosome is a kind of biological nano-vesicle with a diameter of about 30-100 nm and is synthesized, secreted, and released in almost all types of body cells. Recent studies have found that exosomes contain a variety of functional proteins, including mRNA and microRNAs (miRNAs) and so on, which play an important role in the process of material transfer and information exchange in cells. In addition, the related-exosomal microRNAs secreted by tumor cells play an important role in regulating theoccurrence, development, invasion and metastasis of tumors and other biological processes.. Therefore, the study of tumor-related exosomal microRNAs will help us to explore the mechanism of tumor progression from the perspective of tumor gene regulation and new tumor markers, which will contribute to the early diagnosis, treatment, disease monitoring and prognosis evaluation.

Adult-onset leukoencephalopathy with axonal spheroids and pigmented glia(ALSP)is a clinically rare autosomal dominant genetic disease,and its specific pathogenesis is not yet clear.The colony-stimulating factor 1 receptor(CSF1R)is a transmembrane tyrosine kinase receptor on the cell surface and mutations in the gene encoding it have been identified as potential pathogenic factors for ALSP.However,the specific mechanisms by which CSF1R gene mutations lead to the onset of ALSP are still unclear.After reviewing the mutation sites and pathogenic mechanisms of CSF1R in the pathogenesis of ALSP,CSF1R mutations have been shown to cause microglial dysfunction through mechanisms such as dominant-negative effects,loss of function,haploinsufficiency,and gain of function,thereby leading to the onset of ALSP.A deeper understanding of the causes of ALSP will help in exploring potential treatment methods.

Motor imagery (MI), motion intention of the specific body without actual movements, has attracted wide attention in fields as neuroscience. Classification algorithms for motor imagery electroencephalogram (MI-EEG) signals are able to distinguish different MI tasks based on the physiological information contained by the EEG signals, especially the features extracted from them. In recent years, there have been some new advances in classification algorithms for MI-EEG signals in terms of classifiers versus machine learning strategies. In terms of classifiers, traditional machine learning classifiers have been improved by some researchers, deep learning and Riemannian geometry classifiers have been widely applied as well. In terms of machine learning strategies, ensemble learning, adaptive learning, and transfer learning strategies have been utilized to improve classification accuracies or reach other targets. This paper reviewed the progress of classification algorithms for MI-EEG signals, summarized and evaluated the existing classifiers and machine learning strategies, to provide new ideas for developing classification algorithms with higher performance.
Algorithms ; Brain-Computer Interfaces ; Electroencephalography ; Imagery, Psychotherapy ; Imagination ; Machine Learning