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 analyze the clinical characteristics,treatment,and prognosis of immune checkpoint inhibitor-related diabetes mellitus(ICI-DM).Methods The clinical characteristics,laboratory examinations,treatment regimens,and follow-up outcomes of 10 ICI-DM patients who were diagnosed and treated in the First Medical Center of Chinese PLA General Hospital between July 2019 and December 2024 were retrospectively analyzed.Relevant literatures were retrieved from domestic and foreign databases such as PubMed,CNKI,and VIP.The clinical characteristics of ICI-DM were summarized based on the literature results.Results All 10 patients were PD-1 inhibitor users,including 5 males and 5 females,with a median age of 54.5(51.3,64.0)years and a body mass index(BMI)of(22.0±2.15)kg/m2.Among them,9 cases(90.0%)were fulminant type 1 diabetes mellitus(FT1DM);9 cases(90.0%)had a severity of adverse events reaching grade 3-4 according to the Common Terminology Criteria for adverse events(CTCAE).The median time from PD-1 inhibitor treatment to the occurrence of the classic diabetes symptoms referred to as"three more and one less"(polyuria,polydipsia,polyphagia,and weight loss)in all patients was 145.5(110.5,204.8)days,and the medication duration was 6.0(4.3,7.8)cycles.The average blood glucose level of the 10 patients at the time of consultation was 25.3(10.0-41.4)mmol/L,and the glycated hemoglobin(HbA1c)level was 8.0%(6.6%-10.9%).Eight patients had fasting and 2-hour C-peptide levels<0.1 ng/ml(fasting C-peptide from<0.010 to 0.067 ng/ml,2-hour C-peptide from<0.010 to 0.077 ng/ml).Nine of the 10 patients were negative for diabetes autoantibodies,while 1 was not tested.All 10 patients were successfully treated with insulin and other therapies.During the follow-up after discharge,all patients still relied on insulin treatment,and no significant recovery of pancreatic islet β cell function was observed compared with that at discharge.Literature review revealed that ICI-DM was more common in PD-1 inhibitor users,with clinical mainly manifested as diabetic ketoacidosis(DKA)(65.4%)and diabetic ketosis(13.1%).Patients had severely impaired pancreatic islet function and required long-term insulin treatment,and some cases were complicated by thyroid or pituitary dysfunction.Conclusions ICI-DM typically presents as FT1DM,often manifesting with DKA or diabetic ketosis at onset.It is characterized by severe and irreversible loss of pancreatic islet function,necessitating lifelong insulin therapy.To enable early detection and prompt treatment,close monitoring of blood glucose is essential during ICI treatment.

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]

Objective To explore the relationship between insulin resistance and idiopathic central precocious puberty(ICPP)in girls and the diagnostic value of insulin resistance.Methods Clinical data of 245 girls aged 4 to 7.5 years with low luteinizing hormone(LH)levels(0.2-0.83 IU/L),normal body weight(body mass index standard deviation score between-2 and+2),and early breast development who visited the Department of Pediatric Endocrinology,Henan Provincial Maternal and Child Health Hospital from January 2022 to March 2025 were retrospectively analyzed.According to the Expert Consensus on the Diagnosis and Treatment of Central Precocious Puberty(2022),patients were assigned to an ICPP group(n=123)or a control group(n=122).Correlations between the homeostasis model assessment of insulin resistance(HOMA-IR)and selected indices were assessed.Multivariable logistic regression was used to evaluate the association between HOMA-IR and ICPP,and the diagnostic performance of various indices for ICPP was evaluated.Results HOMA-IR was higher in the ICPP group than in the control group(P<0.001)and was positively correlated with LH peak(rs=0.467,P<0.05)and the LH peak/FSH peak ratio(rs=0.444,P<0.05).The multivariable logistic regression model including age,BMI,and basal LH showed that HOMA-IR was closely associated with ICPP(OR=2.756,95%CI:1.940-3.913).Receiver operating characteristic curve analysis showed that the areas under the curve for basal LH,HOMA-IR,and their combination in diagnosing ICPP were 0.735,0.735,and 0.805,respectively(P<0.05),and the combined model had a greater area under the curve than either basal LH or HOMA-IR alone(both P<0.05).Conclusions HOMA-IR is closely associated with ICPP in girls with low LH and normal body weight,and combining HOMA-IR with basal LH improves early identification and diagnostic efficiency in this population.

Objective To explore the relationship between insulin resistance and idiopathic central precocious puberty(ICPP)in girls and the diagnostic value of insulin resistance.Methods Clinical data of 245 girls aged 4 to 7.5 years with low luteinizing hormone(LH)levels(0.2-0.83 IU/L),normal body weight(body mass index standard deviation score between-2 and+2),and early breast development who visited the Department of Pediatric Endocrinology,Henan Provincial Maternal and Child Health Hospital from January 2022 to March 2025 were retrospectively analyzed.According to the Expert Consensus on the Diagnosis and Treatment of Central Precocious Puberty(2022),patients were assigned to an ICPP group(n=123)or a control group(n=122).Correlations between the homeostasis model assessment of insulin resistance(HOMA-IR)and selected indices were assessed.Multivariable logistic regression was used to evaluate the association between HOMA-IR and ICPP,and the diagnostic performance of various indices for ICPP was evaluated.Results HOMA-IR was higher in the ICPP group than in the control group(P<0.001)and was positively correlated with LH peak(rs=0.467,P<0.05)and the LH peak/FSH peak ratio(rs=0.444,P<0.05).The multivariable logistic regression model including age,BMI,and basal LH showed that HOMA-IR was closely associated with ICPP(OR=2.756,95%CI:1.940-3.913).Receiver operating characteristic curve analysis showed that the areas under the curve for basal LH,HOMA-IR,and their combination in diagnosing ICPP were 0.735,0.735,and 0.805,respectively(P<0.05),and the combined model had a greater area under the curve than either basal LH or HOMA-IR alone(both P<0.05).Conclusions HOMA-IR is closely associated with ICPP in girls with low LH and normal body weight,and combining HOMA-IR with basal LH improves early identification and diagnostic efficiency in this population.

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]

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.

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

Acori Tatarinowii Rhizoma is the dried rhizome of Acorus tatarinowii in the family of Tennantiaceae, which has the efficacy of opening up the orifices and expelling phlegm, awakening the mind and wisdom, and resolving dampness and opening up the stomach. Modern studies have shown that volatile oil is the main active ingredient of Acori Tatarinowii Rhizoma, and α-asarone and β-asarone have been proved to be the active ingredients in the volatile oil of Acori Tatarinowii Rhizoma, with pharmacological effects such as anti-Alzheimer's disease, antiepileptic, anti-Parkinson's disease, antidepressant, anticerebral ischemia/reperfusion injury, anti-thrombosis, lipid-lowering, and antitumor. By summarising and outlining the pharmacological effects of α-asarone and β-asarone and elucidating the possible mechanisms of their pharmacological effects, we can provide theoretical basis for the further research and clinical application of Acori Tatarinowii Rhizoma.
Allylbenzene Derivatives ; Acorus/chemistry* ; Anisoles/chemistry* ; Rhizome/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Humans ; Animals