Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Objective:To investigate the effects of psychosocial factors on early puberty and its sex specific differences.Methods:Bengbu Yuhui Longitudinal Study of Children Development Cohort, consisting of 1 162 students in grades 1-3 (524 girls) and their parents, was established in April 2021 in Bengbu, Anhui Province. The parents were surveyed by questionnaire to collect the information about their children's 56 items of psychosocial factor exposures, including 5 dimensions: major life events, early life adversity, interpersonal/relational conflict, family economic status and daily life troubles. Pubertal growth and physical examinations were conducted by trained professionals at baseline, the 1 st (May 2022), 2 nd (October 2022), 3 rd (May 2023), and 4 th (October 2023) follow-up surveys. In this study, the pubertal development status data were from the 4 th follow-up examination. Fianally, the valid data on pubertal development of 1 105 children were obtained, including the data from 510 girls (46.15%). Multinomial logistic regression model was used to analyze the association between psychosocial factors and early puberty, and the final predictors of early puberty were explored by using four models [least absolute shrinkage and selection operator (LASSO), multiple logistic regression, ridge regression, and Bayesian]. Results:The detection rates of early puberty in boys and girls were 13.60% and 16.30%, respectively. The median of intra-group absolute correlation of psychosocial factor exposure (0.042-0.066) was generally higher than that of inter-group among girls (0.031-0.059), while no similar diference was found among boys. LASSO model showed that moving house, being raised by someone other than parents, sexual abuse, peer conflict, high monthly household income, and high exposure to electronics on school days were predictors of early puberty in girls, while moving house and high monthly household income were the predictors of early puberty in girls in all four models (LASSO, multiple logistic regression, ridge regression, and Bayesian). Among boys, only a transient loss from family was a predictor of early puberty.Conclusion:Early puberty in children can be predicted by psychosocial factors, and there are gender-specific differences.

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]

Image 1.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

OBJECTIVE: To evaluate the safety and effectiveness of robot-assisted percutaneous coronary intervention (R-PCI) compared to traditional manual percutaneous coronary intervention (M-PCI). METHODS: This prospective, multicenter, randomized controlled, non-inferior clinical trial enrolled patients with coronary heart disease who met the inclusion criteria and had indications for elective percutaneous coronary intervention. Participants were randomly assigned to either the R-PCI group or the M-PCI group. Primary endpoints were clinical and technical success rates. Clinical success was defined as visually estimated residual post-percutaneous coronary intervention stenosis < 30% with no 30-day major adverse cardiac events. Technical success in the R-PCI group was defined as successful completion of percutaneous coronary intervention using the ETcath200 robot-assisted system, without conversion to M-PCI in the event of a guidewire or balloon/stent catheter that was unable to cross the vessel or was poorly supported by the catheter. Secondary endpoints included total procedure time, percutaneous coronary intervention procedure time, fluoroscopy time, contrast volume, operator radiation exposure, air kerma, and dose-area product. RESULTS: The trial enrolled 152 patients (R-PCI: 73 patients, M-PCI: 79 patients). Lesions were predominantly B2/C type (73.6%). Both groups achieved 100% clinical success rate. No major adverse cardiac events occurred during the 30-day follow-up. The R-PCI group had a technical success rate of 100%. The R-PCI group had longer total procedure and fluoroscopy times, but lower operator radiation exposure. The percutaneous coronary intervention procedure time, contrast volume, air kerma, and dose-area product were similar between the two groups. CONCLUSIONS For certain complex lesions, performing percutaneous coronary intervention using the ETcath200 robot-assisted system is safe and effective and does not result in conversion to M-PCI.

OBJECTIVE: To assess the value of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) score combined with PSA density (PSAD) in the diagnosis of clinically significant prostate cancer (CSPCa) in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy. METHODS: This retrospective study included 327 male patients with total PSA (tPSA) levels of 4-10 μg/L undergoing MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy in our hospital between January 2021 and December 2023. According to the pathological results, we divided the patients into a CSPCa (n = 44) and a non-CSPCa group (n = 283), collected their clinical and imaging data, and subjected them to statistical analysis. RESULTS: The age, tPSA level, PSAD and PI-RADS score were significantly higher, while the free PSA (fPSA) level, f/tPSA ratio and prostate volume remarkably lower in the CSPCa than in the non-CSPCa group (P<0.05). The areas under the curve (AUCs) of PSAD, PI-RADS score and their combination were 0.772, 0.730 and 0.801, with sensitivities of 63.63%, 70.45% and 72.73%, and specificities of 84.10%, 75.62% and 83.75%, respectively (P<0.01). With PSAD 0.2 μg/(ml·cm3) as the best cut-off value and based on the PI-RADS scores, the patients were divided into two groups for analysis. In the patients with PI-RADS scores 2 and 5, the AUCs were 0.534 and 0.643, with sensitivities of 16.67% and 63.64%, and specificities of 85.14% and 64.29%, with no statistically significant differences (P= 0.784, P= 0.228), and in those with PI-RADS scores 3 and 4, the AUCs were 0.794 and 0.843, with sensitivities of 57.14% and 80.00%, and specificities of 87.14% and 81.82%, with statistically significant differences (P= 0.009, P<0.001). CONCLUSION PI-RADS v2.1 score combined with PSAD can effectively improve the diagnostic efficiency of CSPCa in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy and serve as a guide for selection of prostate biopsy.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Retrospective Studies ; Prostate-Specific Antigen ; Magnetic Resonance Imaging ; Image-Guided Biopsy ; Prostate/pathology* ; Aged ; Middle Aged

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]

Objective:To investigate the effects of psychosocial factors on early puberty and its sex specific differences.Methods:Bengbu Yuhui Longitudinal Study of Children Development Cohort, consisting of 1 162 students in grades 1-3 (524 girls) and their parents, was established in April 2021 in Bengbu, Anhui Province. The parents were surveyed by questionnaire to collect the information about their children's 56 items of psychosocial factor exposures, including 5 dimensions: major life events, early life adversity, interpersonal/relational conflict, family economic status and daily life troubles. Pubertal growth and physical examinations were conducted by trained professionals at baseline, the 1 st (May 2022), 2 nd (October 2022), 3 rd (May 2023), and 4 th (October 2023) follow-up surveys. In this study, the pubertal development status data were from the 4 th follow-up examination. Fianally, the valid data on pubertal development of 1 105 children were obtained, including the data from 510 girls (46.15%). Multinomial logistic regression model was used to analyze the association between psychosocial factors and early puberty, and the final predictors of early puberty were explored by using four models [least absolute shrinkage and selection operator (LASSO), multiple logistic regression, ridge regression, and Bayesian]. Results:The detection rates of early puberty in boys and girls were 13.60% and 16.30%, respectively. The median of intra-group absolute correlation of psychosocial factor exposure (0.042-0.066) was generally higher than that of inter-group among girls (0.031-0.059), while no similar diference was found among boys. LASSO model showed that moving house, being raised by someone other than parents, sexual abuse, peer conflict, high monthly household income, and high exposure to electronics on school days were predictors of early puberty in girls, while moving house and high monthly household income were the predictors of early puberty in girls in all four models (LASSO, multiple logistic regression, ridge regression, and Bayesian). Among boys, only a transient loss from family was a predictor of early puberty.Conclusion:Early puberty in children can be predicted by psychosocial factors, and there are gender-specific differences.