OBJECTIVES: To study clinical manifestations and gene mutation features of neonates with centronuclear myopathy. METHODS: A retrospective analysis was conducted on the medical data of 5 neonates with centronuclear myopathy diagnosed in the Neonatal Intensive Care Unit of Children's Hospital, Zhejiang University School of Medicine from January 2020 to August 2024. The data included gender, gestational age, birth weight, Apgar score, clinical manifestations, creatine kinase level, electromyography, genetic testing results and the outcomes of the infants. RESULTS: All 5 male neonates had a history of postpartum asphyxia and resuscitation. They all presented with hypotonia, myasthenia, and respiratory failure; two neonates also had swallowing dysfunction. Of the five neonates, three had normal creatine kinase levels, while two had slightly elevated levels. Electromyography was performed for three neonates, among whom two had myogenic damage. MTM1 gene mutations were identified by genetic testing in all five neonates, including two nonsense mutations and three missense mutations, among which one variant had not been previously reported. Four mutations were inherited from the mother, and the other one was a de novo mutation. The five neonates showed no clinical improvement following treatment, failed weaning from mechanical ventilation, and ultimately died after withdrawal of life-sustaining therapy. CONCLUSIONS Centronuclear myopathy caused by MTM1 gene mutation often has a severe phenotype and a poor prognosis, and it should be considered for neonates with hypotonia and myasthenia after birth. Genetic testing should be performed as soon as possible.
Humans ; Myopathies, Structural, Congenital/genetics* ; Male ; Infant, Newborn ; Retrospective Studies ; Mutation ; Female ; Protein Tyrosine Phosphatases, Non-Receptor/genetics*

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

Pharmacotranscriptomic profiles, which capture drug-induced changes in gene expression, offer vast potential for computational drug discovery and are widely used in modern medicine. However, current computational approaches neglected the associations within gene‒gene functional networks and unrevealed the systematic relationship between drug efficacy and the reversal effect. Here, we developed a new genome-scale functional module (GSFM) transformation framework to quantitatively evaluate drug efficacy for in silico drug discovery. GSFM employs four biologically interpretable quantifiers: GSFM_Up, GSFM_Down, GSFM_ssGSEA, and GSFM_TF to comprehensively evaluate the multi-dimension activities of each functional module (FM) at gene-level, pathway-level, and transcriptional regulatory network-level. Through a data transformation strategy, GSFM effectively converts noisy and potentially unreliable gene expression data into a more dependable FM active matrix, significantly outperforming other methods in terms of both robustness and accuracy. Besides, we found a positive correlation between RS_GSFM and drug efficacy, suggesting that RS_GSFM could serve as representative measure of drug efficacy. Furthermore, we identified WYE-354, perhexiline, and NTNCB as candidate therapeutic agents for the treatment of breast-invasive carcinoma, lung adenocarcinoma, and castration-resistant prostate cancer, respectively. The results from in vitro and in vivo experiments have validated that all identified compounds exhibit potent anti-tumor effects, providing proof-of-concept for our computational approach.

Based on FangNet platform,the data of the prescriptions for the effective cases of post-stroke sequelae treated by national renowned Chinese medical practitioner LIU Mao-Cai were collected for the analysis of medication frequency of the prescribed drugs as well as their properties,flavors and meridian tropism.The medication rules of LIU Mao-Cai for treating post-stroke sequelae was summarized by analyzing the weight scale,co-occurrence and mutual exclusivity of the prescribed drugs and by drug-symptom association rule analysis and drug clustering analysis.The results showed that a total of 105 prescriptions involving 95 Chinese medicines were obtained.The drugs in the prescriptions were mainly warm in nature,sweet in flavor and had the meridian tropism of liver meridian.There were 17 driver herbs,and they were Astragali Radix,Gastrodiae Rhizoma,Corni Fructus,Codonopsis Radix,Eucommiae Cortex,Achyranthis Bidentatae Radix,Chuanxiong Rhizoma,Polygalae Radix,Curcumae Longae Rhizoma,Acori Tatarinowii Rhizoma,Ophiopogonis Radix,Atractylodis Macrocephalae Rhizoma,Salviae Miltiorrhizae Radix et Rhizoma,Poria,Uncariae Ramulus cum Uncis,Pinelliae Rhizoma Praeparatum,and Ligustri Lucidi Fructus.The results of drug co-occurrence analysis yielded 12 drug pairs such as Achyranthis Bidentatae Radix-Eucommiae Cortex,drug-symptom association rule analysis yielded 9 groups of drug-symptom association combinations such as Gastrodiae Rhizoma-dizziness,and cluster analysis yielded 4 drug combinations.The results indicated that the drugs for post-stroke sequelae treated by LIU Mao-Cai are mild in nature and mainly have the actions of supporting healthy-qi and replenishing the deficient,and Astragali Radix and Codonopsis Radix are often used to replenish the vital energy,and Corni Fructus,Achyranthis Bidentatae Radix and Eucommiae Cortex are usually used to tonify the liver and kidney.Moreover,simultaneous treatment of phlegm and blood stasis,and simultaneous application of purging and nourishing therapeutics are also stressed.

Magnetic cell sorting technology is a highly specific and rapid cell sorting technology using superparamagnetic nanocomposites for cell sorting, which is widely used in immunology, stem cytology, oncology, clinical medicine and other fields. Magnetic cell sorting technology is divided into positive isolation, negative isolation/untouched cell isolation, depletion, multi-step isolation and automated cell separation systems. In this review, we firstly give a brief introduction to the classification and application of magnetic cell sorting technology, then discuss several new techniques and challenges based on magnetic cell sorting in recent years, such as improving the sorting efficiency by improving the structure of magnetic materials and magnetic field structure. The necessity of biological evaluation of magnetic cell sorting products was emphatically analyzed. Through the biological evaluation, the advantages and disadvantages of magnetic cell sorting products can be understood, and the research and development ability could be improved. Therefore, 10 biological evaluation technical parameters related to magnetic cell sorting products were proposed: yield, purity, sterility, cytotoxicity, cell morphology, viability, light scattering characteristics of cells, fluorescent antibody labeling ability of cells, cell activation and cell proliferation. The 10 biological evaluation technical parameters play an important role in promoting the standardized application of magnetic cell sorting.

Objective: To explore mental health status of vocational college students and its association with physical exercise and exercise motivation, so as to provide data support for the promotion of physical exercise, exercise motivation theory and the protection of mental health among vocational college students. Methods: From June 2 to July 2, 2023, a convenience sampling method was used to select 1 763 college students from three vocational colleges in Sichuan, Chongqing, and Guizhou for the survey. Physical Activity Rating Scale (PARS-3), Motives for Physical Activities Measure-Revised (MPAM-R), Patient Health Questionnaire-9 (PHQ-9) and Flourishing Scale (FS) were used to assess physical exercise, exercise motivation, depressive symptoms and flourishing levels of vocational college students. Multiple linear regression analysis was conducted to examine the relationship between physical exercise, exercise motivation, depression as the negative indicator of mental health and flourishing as the positive indicator of mental health. Results: There were negative correlations between physical exercise, exercise motivation and their five factors with depression scores among vocational college students ( r=-0.162--0.133, P <0.01). Physical exercise, health motivation and pleasure motivation were positively correlated with flourishing and its eight factors among vocational college students ( r= 0.054 -0.099, P <0.05). Depression scores and flourishing scores varied significantly across students with different levels of physical exercise and exercise motivation ( F=11.18-15.69, 2.80-16.05, P <0.05). Multiple linear regression analysis indicated that physical exercise, health motivation, and total exercise motivation scores were negatively correlated with depressive symptoms ( β = -0.02 , -0.11, -0.35), and physical exercise, health motivation, pleasure motivation, and total exercise motivation scores were positively correlated with flourishing ( β =0.31, 0.32, 0.50, 0.30) ( P <0.05). Conclusions Physical exercise and exercise motivation are significantly associated with mental health of vocational college students. Enhancing physical exercise and increasing exercise motivation in aspects of health and pleasure can promote mental health of vocational college students.

ObjectiveGlutathione (γ-glutamyl-L-cysteinylglycine, GSH) is the most abundant non-protein compound containing sulfhydryl (―SH) groups in cells. It serves as a source of reducing equivalents, effectively neutralizing harmful reactive substances, and playing a crucial role in maintaining cellular redox balance. Therefore, sensitive detection and accurate measurement of GSH levels in tissues are of great importance. In this work, we presents a novel method for GSH detection utilizing electron paramagnetic resonance (EPR) spectroscopy. MethodsInitially, ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate acid)) solution was mixed with K₂S₂O₈ solution and reacted in the dark for 12 to 16 h to prepare ABTS·⁺ solution, which was then quantified using UV-Vis spectroscopy. Subsequently, the concentration of glutathione (GSH) was determined based on the changes in the EPR signal of ABTS·⁺. On this basis, the optimal reaction time and temperature were explored to establish a standard equation correlating the EPR signal intensity of ABTS·⁺ with GSH concentration. Finally, the derived standard curve was employed to quantitatively analyze the GSH concentration in whole blood from C57BL/6J mice, and the results were compared with those reported in the literature to verify the accuracy of the method. ResultsThe experimental results demonstrate that this method has a linear detection range from50 nmol/L to 15 μmol/L for GSH, spanning two orders of magnitude, with a limit of detection (LOD) at0.50 nmol/L. The measured GSH content in mouse whole blood is (10 660±706) nmol/g Hb, which agrees with the value of (11 200±237) nmol/g Hb as previously reported. Furthermore, a similar method was developed for detection of glutathione disulfide (GSSG) at higher reaction temperature. ConclusionThis article presents a novel assay for the rapid detection of GSH using the intensity of EPR signal from ABTS·⁺ as indicator. This method demonstrates enhanced detection sensitivity and a broader linear range compared to conventional colorimetric methods. Furthermore, we have extended the application of this method to detect GSH content in blood samples efficiently and accurately, offering valuable information for assessing tissue redox balance, thus holding significant potentials.

Objective:To explore the correlation between peripheral blood B cell count and clinical features and prognosis of patients with newly diagnosed diffuse large B-cell lymphoma(DLBCL).Methods:The relationship of peripheral blood B cell count with clinical features,laboratory indexes and prognosis in 67 patients with newly diagnosed DLBCL was retrospectively analyzed.Results:Patients were divided into low B-cell count group(B cell＜0.1 × 109/L,n=34)and high B-cell count group(B cell≥0.1 × 109/L,n=33)according to the median B cell count values.Compared with the high B cell count group,the low B cell count group had a higher proportion of patients with Lugano stage Ⅲ-Ⅳ,elevated LDH,elevated β2-MG and IPI score 3-5 and increased CRP(P=0.033,0.000,0.023,0.001,0.033).The peripheral CD3+and CD4+cell counts of patients in the low B cell count group were significantly lower than those in the high B cell count group(P=0.010,0.017).After initial treatment,overall response rate(ORR)and complete remission(CR)rate in high B cell count group were significantly higher than those in low B cell count group(P=0.032,0.013).The median follow-up time of patients was 23(2-77)months,progression-free survival(PFS)and overall survival(OS)of patients in the high B cell count group were significantly better than those in the low B cell count group(P=0.001,0.002).Univariate analysis showed that pretreatment low B cell count in the peripheral blood was associated with shortened PFS and OS(HR=4.108,P=0.002;HR=8.218,P=0.006).Multivariate analysis showed that low B cell count was an independent prognostic factor for shortened PFS(HR=3.116,P=0.037).Conclusion:Decreased peripheral blood B cell count in newly diagnosed DLBCL patients is associated with high-risk clinical features and may affect the efficacy of immunochemotherapy,which is associated with poor clinical prognosis.

Objective To observe the value of CT radiomics for differentiating spinal bone islands(BI)and osteoblastic metastases(OBM).Methods Data of 109 BI lesions in 98 patients and 282 OBM lesions in 158 patients(including 103 OBM in 48 lung cancer cases,86 OBM in 52 breast cancer cases and 93 OBM in 58 prostate cancer cases)from 3 medical institutions were retrospectively analyzed.Data obtained from institution 1 were used as the internal dataset and divided into internal training set and internal validation set at a ratio of 7∶3,from institution 2 and 3 were used as external dataset.All datasets were divided into female data subset(including OBM of female lung cancer and breast cancer)and male data subset(including OBM of male lung cancer and prostate cancer).Radiomics features were extracted and screened to construct 3 different support vector machine(SVM)models,including model1 for distinguishing BI and OBM,model2 for differentiating OBM of female lung cancer and breast cancer,and model3 for differentiating OBM of male lung cancer and prostate cancer.Diagnostic efficacy of model1,CT value alone and 3 physicians(A,B,C)for distinguishing BI and OBM were assessed,as well as differentiating efficacy for different OBM of model2 and model3.Receiver operating characteristic(ROC)curves were drawn,and area under the curves(AUC)were calculated and compared.The differential diagnostic efficacy of model2 and model3 were also assessed with ROC analysis and AUC.Results AUC of model1 for distinguishing spinal OBM from BI in internal training set,internal validation set and external dataset was 0.99,0.98 and 0.86,respectively.In internal training set,model1 had higher AUC for distinguishing BI and OBM than that of physician A(AUC=0.78),B(AUC=0.87)and C(AUC=0.93)as well as that of mean CT value(AUC=0.78,all P＜0.05).AUC in internal training set,internal validation set and external dataset of model2 for identifying female lung cancer and breast cancer OBM was 0.79,0.75 and 0.73,respectively,of model3 for discriminating male lung cancer from prostate cancer OBM was 0.77,0.74 and 0.77,respectively.Conclusion CT radiomics SVM model might reliablely distinguish OBM and BI.