Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Iron is one of the essential trace elements for the human body,which is crucial for the growth and development of newborns,especially premature infants.It participates in the generation of hemoglobin,affects the activity of various enzymes,and subsequently affects neurometabolism,neurochemistry,neuroanatomy,and gene/protein composition,thereby having a lasting impact on the development of the central nervous system.This article reviews the research progress on the relationship between iron metabolism and neurodevelopment in premature infants in recent years,aiming to provide scientific basis for clinical management and preventive intervention of premature infants.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Iron is one of the essential trace elements for the human body,which is crucial for the growth and development of newborns,especially premature infants.It participates in the generation of hemoglobin,affects the activity of various enzymes,and subsequently affects neurometabolism,neurochemistry,neuroanatomy,and gene/protein composition,thereby having a lasting impact on the development of the central nervous system.This article reviews the research progress on the relationship between iron metabolism and neurodevelopment in premature infants in recent years,aiming to provide scientific basis for clinical management and preventive intervention of premature infants.

NLRP3 can recruit proteins such as ASC and pro-caspase1 to form NLRP3 inflammasomes after being stimulated by pathogen and danger signals in vivo,and then induce pyropto-sis and promote the inflammatory reactions to maintain the home-ostasis.However,the overactivation of NLRP3 inflammasomes is closely related to many inflammatory and autoimmune diseases in humans.Targeted inhibition of NLRP3 inflammasomes can sig-nificantly inhibit inflammation and alleviate the relative symp-toms.Therefore,it is an important research direction for treating diseases of NLRP3 inflammasome that searching for effective in-hibitors targeting NLRP3 inflammasome activation and achieving clinical transformation.This review summarizes the latest re-search progress based on the sources of NLRP3 inflammasome inhibitors.

ObjectiveTo investigate the influence of E2F transcription factor 2 （E2F2） on the cell adhesion of multiple myeloma cells by combining bioinformatics and cellular and molecular experiments. MethodsFirstly， clinical samples and GEO database were used to analyze the relationship between the E2F2 expression and the prognosis of myeloma patients. Then， differential genes were screened from the RNA-seq data of E2F2 knockdown myeloma cell line MM.1S. The GO biological function enrichment and KEGG signal pathway analysis were performed on these differential genes. Meanwhile， the protein interaction network was analyzed by using the string website. The E2F2 stable knockdown MM.1S cell line were constructed， and the expression level of E2F2 was measured by Western Blotting and qRT-PCR. The effect of stable knockdown E2F2 on the adhesion of myeloma cells was detected by cell adhesion experiment， and the expression of cell adhesion related genes were detected by qRT-PCR. The effect of stable E2F2 knockdown on myeloma cell migration was detected by cell migration assay. ResultsThe expression of E2F2 was significantly increased in clinical samples of myeloma patients， and the high expression of E2F2 is correlated with poor prognosis of myeloma patients in the GEO database. The analysis of RNA-seq data revealed 815 differentially expressed genes， of which 508 genes were up-regulated and 307 genes were down-regulated. These genes were closely related to the cell adhesion and angiogenesis. The construction of E2F2 knockdown MM.1S cell lines were verified by Western Blotting and qRT-PCR. Knockdown of E2F2 significantly increased the adhesion level of MM.1S cells and elevated the expression of FN1， PECAM1， ICOSLG and other cell adhesion related genes， while weakening the invasion ability of MM.1S cells， P < 0.05. ConclusionsThrough bioinformatics analysis of the RNA-seq data， we found that the transcription factor E2F2 is closely related to the cell adhesion in myeloma. Knockdown of E2F2 in the MM.1S cell line promotes the expression of cell adhesion related genes， increases the cell adhesion level， and inhibites cell migration ability.

Objective To investigate the risk factors of adult urolithiasis in China. Methods 14 areas including 11 communities and 19 villages were randomly selected from 7 provinces of China by multi-stage stratified cluster sampling method during the period of May 2013 to July 2014. Individuals were investigated by a face-to-face questionnaire and a physical examination including urinary tract ultrasonographic examinations, routine blood and urine tests and blood biochemical examination ect. Results In total, 1 447 participants were found with the urolithiasis among 9 310 individuals and the overall prevalence was 15.5% (1 447/9 310). The prevalence of urolithiasis was significantly different among 14 areas ( 2=711.523，P<0.001), the lowest was the village in Shanxi (0.76%) and the highest was the village in Guangdong(35.99%). The intercept-only model further indicated the reginal aggregation for the individuals of urolithiasis (t=2.48, P=0.027) and the ICC was 48.74%. The two-level Logistic regression model showed that the gender (OR=1.235, 95% CI:1.082-1.411, P=0.005), age (OR=1.101, 95% CI:1.047-1.158, P=0.001), diabetes mellitus (OR=1.411，95%CI:1.192-1.670, P=0.001), family history of urinary calculi (OR=1.867, 95% CI:1.500-2.323, P<0.001), LDL (OR=1.150, 95% CI:1.050-1.260, P=0.006), drinking coffee (OR=1.352, 95% CI:1.065-1.716, P=0.017) and drinking sodas (OR=1.547, 95% CI:1.203-1.990, P=0.002) were the risk factors for urolithiasis. By contrast, consumed more fermented vinegar (OR=0.567, 95% CI:0.498-0.645, P<0.001) and had a amount of legume (OR=0.726, 95% CI:0.628-0.839, P<0.001) were protective factors of urolithiasis. Conclusion The prevalence of urolithiasis among adults reveal an aggregation in area-level, influenced by life environment and dietary habits of individual.

Objective To establish a management system to promote early rehabilitation for work injured patients. Methods The 2015 hospitalized patients were set as control group (n=16,635), and the 2016 hospitalized patients were set as observation group (n=15,372). The control group was hospitalized for injury data collection surveys and was not implemented systematic rehabilitation propaganda, rehabilita-tion assessment and rehabilitation guidance. However, the observation group hospitalized after establishment of the Work Injuries Rehabilita-tion Investigation System and accepted work injuries rehabilitation intervention, such as rehabilitation propaganda, rehabilitation assessment and rehabilitation guidance. The changes of hand trauma rehabilitation indicators were compared between two groups. Results The rate of work injuries rehabilitation intervention was 80.6%in the observation group. In the observation group, the proportion of the patients who re-ceived early rehabilitation treatment in the designated hospital (56.8%) was significantly higher than that of the control group (17.0%) (χ2=2603.683, P<0.001);the proportion of injured patients who were admitted to the designated work injuries rehabilitation institutions (9.4%) was higher than that of the control group (4.3%) (χ2=285.906, P<0.001). The proportion of patients evaluated as disability in the observation group (17.4%) was significantly less than that of the control group (26.3%) (χ2=235.327, P<0.001). The disability score was significantly lower in the observation group (6.23±1.29) than in the control group (8.26±1.16) (t=68.371, P<0.001). Conclusion The Work Injuries Reha-bilitation Investigation System can promote the early rehabilitation for the hand trauma patients in the designated hospital for work injuries, improve the proportion of hand trauma patients to enter the designated work injuries rehabilitation institutions to receive rehabilitation treat-ment, reduce the proportion of disabled persons, and reduce the degree of disability, effectively promote the overall recovery of patients with hand trauma.