Pancreatic cancer has emerged as one of the most challenging malignancies worldwide,with its high resistance to chemotherapy being the primary cause of treatment failure.Therefore,enhancing the chemosensitivity of pancreatic cancer has become a major focus of current research.In this study,we in-vestigated how Bufotaline,a bufadienolide extracted from the traditional Chinese medicine toad venom,exhibits its antitumor activity.Specifically,we explored the potential of Bufotaline to enhance the chemo-sensitivity of pancreatic cancer cells to Adriamycin and elucidated its underlying molecular mechanisms.Using CCK-8 and colony formation assays,we demonstrated that Bufotaline enhances the inhibitory effect of Adriamycin on the survival of pancreatic cancer cell lines Patu-8988T,Aspc-1,and Patu-8988S.No-tably,Bufotaline treatment reduced the IC50 of Adriamycin in drug-resistant pancreatic cancer cells to lev-els comparable to those in non-resistant cells.Results from Western blot,immunofluorescence,comet as-say,and TUNEL assays revealed that Bufotaline promotes Adriamycin-induced DNA damage in pancreatic cancer cells.RNA-seq analysis of Patu-8988T cells treated with Adriamycin alone or in combination with Bufotaline showed significant changes in gene expression,and qRT-PCR analysis further confirmed that Bu-fotaline downregulates the expression of DNA damage repair proteins NBS1 and RAD50.Moreover,Western blot analysis revealed that Bufotaline reduces the levels of DNA damage response repair proteins,and Im-munofluorescence experiments indicated that Bufotaline inhibits the activation of the ATM/CHK2 signaling pathway.Finally,in a subcutaneous xenograft mouse model,the combination of Adriamycin and Bufotaline treatment significantly suppressed pancreatic cancer cell growth.In conclusion,Bufotaline enhances Adria-mycin-induced chemosensitivity in pancreatic cancer cells;the combination of Adriamycin and Bufotaline downregulates the expression of DNA damage response repair proteins NBS1 and RAD50,and inhibits the ATM/CHK2-mediated DDR signaling pathway,thereby delaying DNA damage repair.

Objective To explore the factors that influence major adverse cardiovascular events(MACE)in atrial fibrillation(AF)patients undergoing radiofrequency ablation(RFA),as well as to compare the prognosis of patients with advanced AF to that of the general population.Methods We prospectively recruited AF patients who underwent RFA treatment at Peking University Third Hospital between January 2021 and March 2023.General patient data were collected through the hospital's inpatient system,and MACE were tracked through outpatient visits and telephone follow-ups.Patients were categorized into three age groups:Group 1(under 65 years),Group 2(65 to 75 years),and Group 3(over 75 years).In this study,MACE was defined as include cardiovascular death,all-cause death,readmission for heart failure,acute coronary syndrome(ACS),grade 2 or higher bleeding and stroke.Results A total of 431 patients were included in this study,with an average age of(66.17±12.22)years.Among these patients,259 were male(60.09％),and the mean of CHA2DS2-VASc score was(1.79±1.30).The median follow-up period was 16.0(11.3,21.3)months,during which 28(6.50％)patients experienced MACE,with ACS and stroke being the most common events.Variables were selected using LASSO regression,and a LASSO-Cox regression model was constructed.Age(HR 1.06,95％CI 1.02-1.10,P=0.006)and hypertrophic cardiomyopathy(HR 3.70,95％CI 1.27-8.68,P=0.008)were identified as independent predictors of MACE after RFA for AF.Subgroup analysis revealed that patients under 65 had significantly better prognoses compared to older AF patients(P=0.030 compared with group 2;P=0.021 compared with group 3).Conclusions Age and hypertrophic cardiomyopathy are independent risk factors for MACE in AF patients undergoing RFA.The prognosis for younger patients is better than that for older patients,while the prognosis for advanced patients is comparable to that of patients aged 65-75 years.

Pancreatic cancer has emerged as one of the most challenging malignancies worldwide,with its high resistance to chemotherapy being the primary cause of treatment failure.Therefore,enhancing the chemosensitivity of pancreatic cancer has become a major focus of current research.In this study,we in-vestigated how Bufotaline,a bufadienolide extracted from the traditional Chinese medicine toad venom,exhibits its antitumor activity.Specifically,we explored the potential of Bufotaline to enhance the chemo-sensitivity of pancreatic cancer cells to Adriamycin and elucidated its underlying molecular mechanisms.Using CCK-8 and colony formation assays,we demonstrated that Bufotaline enhances the inhibitory effect of Adriamycin on the survival of pancreatic cancer cell lines Patu-8988T,Aspc-1,and Patu-8988S.No-tably,Bufotaline treatment reduced the IC50 of Adriamycin in drug-resistant pancreatic cancer cells to lev-els comparable to those in non-resistant cells.Results from Western blot,immunofluorescence,comet as-say,and TUNEL assays revealed that Bufotaline promotes Adriamycin-induced DNA damage in pancreatic cancer cells.RNA-seq analysis of Patu-8988T cells treated with Adriamycin alone or in combination with Bufotaline showed significant changes in gene expression,and qRT-PCR analysis further confirmed that Bu-fotaline downregulates the expression of DNA damage repair proteins NBS1 and RAD50.Moreover,Western blot analysis revealed that Bufotaline reduces the levels of DNA damage response repair proteins,and Im-munofluorescence experiments indicated that Bufotaline inhibits the activation of the ATM/CHK2 signaling pathway.Finally,in a subcutaneous xenograft mouse model,the combination of Adriamycin and Bufotaline treatment significantly suppressed pancreatic cancer cell growth.In conclusion,Bufotaline enhances Adria-mycin-induced chemosensitivity in pancreatic cancer cells;the combination of Adriamycin and Bufotaline downregulates the expression of DNA damage response repair proteins NBS1 and RAD50,and inhibits the ATM/CHK2-mediated DDR signaling pathway,thereby delaying DNA damage repair.

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]

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

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]

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Objective To investigate the influencing factors of grade 3-4 multiple myeloma bone disease(MBD)in newly diagnosed multiple myeloma(NDMM)patients,and establish a risk prediction model based on a nomogram.Methods A total of 261 patients with NDMM who were treated in Ningbo Medical Center Lihuili Hospital from January 2015 to December 2021 were retrospectively selected.The patients were divided into group A(MBD grade 0-2,110 cases)and group B(MBD grade 3-4,151 cases)according to MBD grade at the time of initial diagnosis.Logistic regression analysis was used to screen the risk factors for grade 3-4 MBD in NDMM patients,and the risk prediction model was constructed.The receiver operating characteristic(ROC)curve was used for comprehensive evaluation.Results Multivariate regression analysis showed that age,serum phosphorus,C-reactive protein(CRP),globulin(GLB)and bone marrow plasma cell percentage(BMPCp)were independent risk factors for grade 3-4 MBD in NDMM patients(P<0.05).Based on this,risk prediction model was constructed as follows:logit(P)=-15.092+0.107(age)+1.150(serum phosphorus)+0.057(CRP)+0.040(GLB)+0.212(BMPCp).There was no significant difference between the predicted probability and the actual incidence by the Hosmer-Lemeshow goodness of fit test(P=0.770).The accuracy of the model in predicting grade 3-4 MBD in NDMM patients was 90.40%,and the area under the curve was 0.957(95%CI:0.932-0.981),indicating a reliable prediction ability.Conclusion Age,serum phosphorus,CRP,GLB and BMPCp were all independent risk factors for grade 3-4 MBD in NDMM patients,and the constructed risk prediction model has a relatively good predictive effect on the occurrence of grade 3-4 MBD in NDMM patients.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

ObjectiveTo explore the impacts of material type and loading volume of rigid containers on the hydrogen peroxide low temperature plasma sterilization of thoracoscopic instruments, to identify the best rigid containers and loading volume of thoracoscopic instruments. MethodsThoracoscopic instruments sterilized by STERRAD^® 100NX hydrogen peroxide low temperature plasma in Shanghai Pulmonary Hospital affiliated to Tongji University from August to September 2024 were selected as the research items. According to the material of rigid containers, the instruments were divided into polyethylene case group (A), stainless steel case group (B) and silicone resin case group (C). In terms of the loading volume, the rigid containers were divided into (loading capacity <80%) groups of 8, 10 and 12 instruments. The results of physical monitoring, the first type of chemical indicator card monitoring, and the five types of card luminal chemical process challenge device (PCD) monitoring of the 9 groups of A8, A10, A12, B8, B10, B12, C8, C10 and C12 were compared and evaluated. ResultsCompared to A8, A10 A12, C8, C10 or C12 groups, the thoracoscope instruments in the stainless steel containers in B8, B10 or B12 group had higher hydrogen peroxide concentrations and shorter elapsed time in the pressure check phases 1 and phases 2, with the differences statistically significant (P<0.05), followed by the silicone resin case group and the polyethylene case group. The nine groups of physical parameter monitoring, the first type of chemical indicator monitoring, and the five types of chemical PCD monitoring for lumen sterilization achieved 100% qualification rates, and there were no significant differences in the qualified rates of sterilization among the 9 groups (P>0.05). ConclusionWhen using hydrogen peroxide low temperature plasma to sterilize thoracoscopic instruments, it is recommended to use stainless steel or silicone resin rigid containers with a controlled loading capacity (≤12) to ensure optimal sterilization quality.