Diabetic cardiomyopathy is a distinct form of cardiomyopathy that can lead to heart failure, arrhythmias, cardiogenic shock, and sudden death. It has become a major cause of mortality in diabetic patients. The pathogenesis of diabetic cardiomyopathy is complex, involving increased oxidative stress, activation of inflammatory responses, disturbances in glucose and lipid metabolism, accumulation of advanced glycation end products (AGEs), abnormal autophagy and apoptosis, insulin resistance, and impaired intracellular Ca²⁺ homeostasis. Recent studies have shown that adenosine monophosphate-activated protein kinase (AMPK) plays a crucial protective role by lowering blood glucose levels, promoting lipolysis, inhibiting lipid synthesis, and exerting antioxidant, anti-inflammatory, anti-apoptotic, and anti-ferroptotic effects. It also enhances autophagy, thereby alleviating myocardial injury under hyperglycemic conditions. Consequently, AMPK is considered a key protective factor in diabetic cardiomyopathy. As part of diabetes prevention and treatment strategies, both pharmacological and exercise interventions have been shown to mitigate diabetic cardiomyopathy by modulating the AMPK signaling pathway. However, the precise regulatory mechanisms, optimal intervention strategies, and clinical translation require further investigation. This review summarizes the role of AMPK in the prevention and treatment of diabetic cardiomyopathy through drug and/or exercise interventions, aiming to provide a reference for the development and application of AMPK-targeted therapies. First, several classical AMPK activators (e.g., AICAR, A-769662, O-304, and metformin) have been shown to enhance autophagy and glucose uptake while inhibiting oxidative stress and inflammatory responses by increasing the phosphorylation of AMPK and its downstream target, mammalian target of rapamycin (mTOR), and/or by upregulating the gene expression of glucose transporters GLUT1 and GLUT4. Second, many antidiabetic agents (e.g., teneligliptin, liraglutide, exenatide, semaglutide, canagliflozin, dapagliflozin, and empagliflozin) can promote autophagy, reverse excessive apoptosis and autophagy, and alleviate oxidative stress and inflammation by enhancing AMPK phosphorylation and its downstream targets, such as mTOR, or by increasing the expression of silent information regulator 1 (SIRT1) and peroxisome proliferator-activated receptor‑α (PPAR‑α). Third, certain anti-anginal (e.g., trimetazidine, nicorandil), anti-asthmatic (e.g., farrerol), antibacterial (e.g., sodium houttuyfonate), and antibiotic (e.g., minocycline) agents have been shown to promote autophagy/mitophagy, mitochondrial biogenesis, and inhibit oxidative stress and lipid accumulation via AMPK phosphorylation and its downstream targets such as protein kinase B (PKB/AKT) and/or PPAR‑α. Fourth, natural compounds (e.g., dihydromyricetin, quercetin, resveratrol, berberine, platycodin D, asiaticoside, cinnamaldehyde, and icariin) can upregulate AMPK phosphorylation and downstream targets such as AKT, mTOR, and/or the expression of nuclear factor erythroid 2-related factor 2 (Nrf2), thereby exerting anti-inflammatory, anti-apoptotic, anti-pyroptotic, antioxidant, and pro-autophagic effects. Fifth, moderate exercise (e.g., continuous or intermittent aerobic exercise, aerobic combined with resistance training, or high-intensity interval training) can activate AMPK and its downstream targets (e.g., acetyl-CoA carboxylase (ACC), GLUT4, PPARγ coactivator-1α (PGC-1α), PPAR-α, and forkhead box protein O3 (FOXO3)) to promote fatty acid oxidation and glucose uptake, and to inhibit oxidative stress and excessive mitochondrial fission. Finally, the combination of liraglutide and aerobic interval training has been shown to activate the AMPK/FOXO1 pathway, thereby reducing excessive myocardial fatty acid uptake and oxidation. This combination therapy offers superior improvement in cardiac dysfunction, myocardial hypertrophy, and fibrosis in diabetic conditions compared to liraglutide or exercise alone.

Objective To investigate the effects of laparoscopic sleeve gastrectomy(LSG)on the cardiac structure and function in obese patients with heart failure(HF)and compare the efficacy of LSG across obese patients with different HF types.Methods This study included 33 obese patients with HF who underwent LSG.The clinical indicators were compared between before operation and 12 months after operation.Repeated measures analysis of variance was employed to evaluate the changes in echocardiographic parameters before operation and 3,6,and 12 months after operation.Patients were allocated into a HF with preserved ejection fraction group(n=17),a HF with mildly reduced ejection fraction group(n=5)and a HF with reduced ejection fraction(HFrEF)group(n=11)based on left ventricular ejection fraction(LVEF)before operation for subgroup analyses of the effects of LSG on the cardiac structure and function of obese patients with HF.The paired samples t-test was conducted to assess the degree of cardiac structural and functional alterations after LSG.Results The 33 patients included 69.7% males,with an average age of(35.3±9.9)years,and a body mass index(BMI)of(51.2±9.8)kg/m².The median follow-up was 9.0(5.0,13.3)months.Compared with the preoperative values,the postoperative BMI(P=0.002),body surface area(BSA)(P=0.009),waist circumference(P=0.010),hip circumference(P=0.031),body fat content(P=0.007),and percentage of patients with cardiac function grades Ⅲ-IV(P<0.001)decreased.At the 12-month follow-up left atrial diameter(P=0.006),right atrial long-axis inner diameter(RAD1)(P<0.001),right atrial short-axis inner diameter(RAD2)(P<0.001),right ventricular inner diameter(P=0.002),interventricular septal thickness at end-diastolic(P=0.002),and left ventricular end-diastolic volumes(P=0.004)and left ventricular end-systolic volumes(P=0.003) all significantly reduced compared with preoperative values.Additionally,left ventricular fractional shortening and LVEF improved(both P<0.001).Subgroup analyses revealed that cardiac structural parameters significantly decreased in the HF with preserved ejection fraction,HF with mildly reduced ejection fraction,and HFrEF subgroups compared with preoperative values.Notably,the HFrEF group demonstrated the best performance in terms of left atrial diameter(P=0.003),left ventricular inner diameter at end-diastole(P=0.008),RAD1(P<0.001),RAD2(P=0.004),right ventricular inner diameter(P=0.019),left ventricular end-diastolic volume(P=0.004)and left ventricular end-systolic volume(P=0.001),cardiac output(P=0.006),tricuspid regurgitation velocity(P=0.002),and pulmonary artery systolic pressure(P=0.001) compared to preoperatively.Postoperative left ventricular fractional shortening(P<0.001,P=0.003,P<0.001)and LVEF(P<0.001,P=0.011,P=0.001)became higher in all the three subgroups than the preoperative values.Conclusions LSG decreased the body weight,BMI,and BSA,improved the cardiac function grade,reversed the enlargement of the left atrium and left ventricle,reduced the right atrium and right ventricle,and enhanced the left ventricular systolic function.It was effective across obese patients with different HF types.Particularly,LSG demonstrates the best performance in improving the structures of both atria and ventricles in obese patients with HFrEF.
Humans ; Male ; Female ; Gastrectomy/methods* ; Heart Failure/complications* ; Adult ; Obesity/physiopathology* ; Laparoscopy ; Middle Aged ; Heart/physiopathology* ; Stroke Volume

In recent years,more and more researches has focused on the correlation between cognitive activity and physiological variables.The change of pupil is regarded as an important target in the cognitive process,and has become a hot research field.This review focuses on the three key brain regions that regulate pupil change,and reflects the neurophysiological mechanism behind pupil change by elaborating the neural pathways related to pupil change and cognitive performance.Based on recent studies on pupil change in cognitive diseases,it aims to promote the application of pupil change in the field of cognitive science in the future.

ObjectiveChemotherapy is one of the important therapeutic approaches for cancer treatment. However, the emergence of multidrug resistance and side effects significantly limit its application. To address these challenges, chemotherapy is often combined with other drugs or therapies. Among the 13 human fucosyltransferases (FUTs) identified, FUT8 (alpha-(1,6)-fucosyltransferase) is the only enzyme responsible for core fucosylation. Core fucosylation plays an important role in cancer occurrence, metastasis and chemotherapy resistance, making the suppression of FUT8 a potential strategy for reversing multidrug resistance. This study aims to evaluate the feasibility of combining the small molecule FUT8 inhibitor 2FF (2-deoxy-2-fluoro-L-fucose) with the clinical chemotherapeutic drug doxorubicin (DOX) for treating malignant tumors. MethodsThe human hepatocellular carcinoma cell line HepG2 and mouse colon cancer cell line CT26 cells were treated with 2FF, DOX or their combination and core fucosylation levels were assessed using Lectin blot. HepG2 and CT26 cells were exposed to 50 μmol/L 2FF for 72 h, followed by treatment with a gradient concentration of DOX for 24 h. Cell viability and IC₅₀ values were determined via the CCK-8 assay. Transwell invasion assays were conducted to evaluate the combined effect of 2FF and DOX on the invasion ability of HepG2 cells. Flow cytometry was performed to analyze the impact of 2FF, DOX and their combination on membrane PD-L1 expression of HepG2 cells. To assess the in vivo effect, 6- to 8-week-old female BALB/c mice (20-25 g), were subcutaneously injected with 1×10⁶ CT26 cells into the right axilla (four groups, six mice in each group). After the average tumor volume reached 100 mm³, mice were treated with DOX, 2FF, their combination, or saline (mock group) every other day. DOX was administrated intraperitoneally (2 mg/kg), 2FF intravenously (5 mg/kg), and the combination group, received the both treatment. Tumor size was measured every other day using a vernier caliper. ResultsThis study demonstrated that DOX upregulates the core fucosylation levels in HepG2 and CT26 cells,while 2FF effectively inhibits this DOX-induced effect. Furthermone, 2FF enhanced the sensitivity of HepG2 and CT26 cells to DOX. The combination of 2FF and DOX synergistically inhibited the invasion ability of HepG2 cells, and enhanced the anti-tumor efficacy of CT26 subcutaneous tumor model in BALB/c mice. However the combination treatment led to weight loss in mice. In addition, DOX increased the cell surface PD-L1 expression in HepG2 cells, which was effectively suppressed by 2FF. ConclusionThe FUT8 inhibitor 2FF effectively suppresses DOX-induced upregulation of core fucosylation and PD-L1 levels in tumor cells, and 2FF synergistically enhances the anticancer efficacy of DOX.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To observe the clinical efficacy and safety of vericiguat tablets combined with sacubitril valsartan sodium(Sac/Val)tablets in the treatment of patients with heart failure with reduced ejection fraction(HFrEF).Methods The HFrEF patients were divided into control group and treatment group according to the cohort method.The control group was treated with Sac/Val tablets 200 mg per time,bid,orally.On the basis of control group,the treatment group was treated with vericiguat tablets 2.5 mg per time,qd,taken with meal.Two groups were treated for 3 months.The clinical efficacy,left ventricular ejection fraction(LVEF),left ventricular end-diastolic dimension(LVEDD)and end-systolic diameter(LVESD),levels of high sensitivity C-reactive protein(hs-CRP),interleukin-6(IL-6),nitric oxide(NO),N-terminal pro-brain natriuretic peptide(NT-proBNP),blood urea nitrogen(BUN)and serum creatinine(SCr),and safety were compared between the two groups.During follow-up,the heart failure rehospitalization rates and major adverse cardiovascular events were compared between the two groups.Results Treatment group was enrolled 53 patients,control group was enrolled 53 patients.After treatment,the total effective rates of treatment and control groups were 94.34％(50 cases/53 cases)and 81.13％(43 cases/53 cases)with statistical significant difference(P＜0.05).After treatment,the LVEF of treatment and control groups were(48.02±5.20)％and(43.02±4.33)％,the LVEDDs were(52.85±6.30)and(55.63±6.88)mm,the LVESDs were(41.64±6.40)and(44.22±5.85)mm,the levels of hs-CRP were(10.22±2.63)and(14.60±2.98)mg L-1,the levels of IL-6 were(14.48±2.40)and(17.36±2.52)pg·mL-1,the levels of NO were(102.60±20.16)and(92.16±16.33)μmol·L-1,the levels of NT-proBNP were(898.74±102.20)and(1315.60±182.64)ng·L-1,the levels of BUN were(12.02±2.28)and(13.45±2.33)mmol·L-1,the levels of SCr were(82.22±5.89)and(85.64±6.03)μmol·L-1,the heart failure rehospitalization rates were 5.66％and 13.21％,respectively;the differences were statistical significant between two groups(all P＜0.05).The adverse drug reactions of treatment group were hyperkalemia,hypotension,renal dysfunction,dizziness and headache,while those in control group were renal dysfunction,hyperkalemia,and hypotension.The major adverse cardiovascular events of treatment group were angina pectoris and acute myocardial infarction,while those in control group were angina pectoris,acute myocardial infarction and atrial fibrillation.The incidences of total adverse drug reactions in treatment and control groups were 13.21％and 7.55％,the incidences of major adverse cardiovascular events were 5.66％and 13.21％,respectively,without statistically significant differences(all P＞0.05).Conclusion Vericiguat tablets combined with Sac/Val tablets have a definitive clinical efficacy in the treatment of HFrEF patients,which can improve cardiac and endothelial function,reduce inflammatory response and readmission times,without increasing the incidences of adverse drug reactions.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To observe the clinical efficacy and safety of vericiguat tablets combined with sacubitril valsartan sodium(Sac/Val)tablets in the treatment of patients with heart failure with reduced ejection fraction(HFrEF).Methods The HFrEF patients were divided into control group and treatment group according to the cohort method.The control group was treated with Sac/Val tablets 200 mg per time,bid,orally.On the basis of control group,the treatment group was treated with vericiguat tablets 2.5 mg per time,qd,taken with meal.Two groups were treated for 3 months.The clinical efficacy,left ventricular ejection fraction(LVEF),left ventricular end-diastolic dimension(LVEDD)and end-systolic diameter(LVESD),levels of high sensitivity C-reactive protein(hs-CRP),interleukin-6(IL-6),nitric oxide(NO),N-terminal pro-brain natriuretic peptide(NT-proBNP),blood urea nitrogen(BUN)and serum creatinine(SCr),and safety were compared between the two groups.During follow-up,the heart failure rehospitalization rates and major adverse cardiovascular events were compared between the two groups.Results Treatment group was enrolled 53 patients,control group was enrolled 53 patients.After treatment,the total effective rates of treatment and control groups were 94.34％(50 cases/53 cases)and 81.13％(43 cases/53 cases)with statistical significant difference(P＜0.05).After treatment,the LVEF of treatment and control groups were(48.02±5.20)％and(43.02±4.33)％,the LVEDDs were(52.85±6.30)and(55.63±6.88)mm,the LVESDs were(41.64±6.40)and(44.22±5.85)mm,the levels of hs-CRP were(10.22±2.63)and(14.60±2.98)mg L-1,the levels of IL-6 were(14.48±2.40)and(17.36±2.52)pg·mL-1,the levels of NO were(102.60±20.16)and(92.16±16.33)μmol·L-1,the levels of NT-proBNP were(898.74±102.20)and(1315.60±182.64)ng·L-1,the levels of BUN were(12.02±2.28)and(13.45±2.33)mmol·L-1,the levels of SCr were(82.22±5.89)and(85.64±6.03)μmol·L-1,the heart failure rehospitalization rates were 5.66％and 13.21％,respectively;the differences were statistical significant between two groups(all P＜0.05).The adverse drug reactions of treatment group were hyperkalemia,hypotension,renal dysfunction,dizziness and headache,while those in control group were renal dysfunction,hyperkalemia,and hypotension.The major adverse cardiovascular events of treatment group were angina pectoris and acute myocardial infarction,while those in control group were angina pectoris,acute myocardial infarction and atrial fibrillation.The incidences of total adverse drug reactions in treatment and control groups were 13.21％and 7.55％,the incidences of major adverse cardiovascular events were 5.66％and 13.21％,respectively,without statistically significant differences(all P＞0.05).Conclusion Vericiguat tablets combined with Sac/Val tablets have a definitive clinical efficacy in the treatment of HFrEF patients,which can improve cardiac and endothelial function,reduce inflammatory response and readmission times,without increasing the incidences of adverse drug reactions.

ObjectiveCellular temperature imaging can assist scientists in studying and comprehending the temperature distribution within cells, revealing critical information about cellular metabolism and biochemical processes. Currently, cell temperature imaging techniques based on fluorescent temperature probes suffer from limitations such as low temperature resolution and a limited measurement range. This paper aims to develop a single-cell temperature imaging and real-time monitoring technique by leveraging the temperature-dependent properties of single-molecule quantum coherence processes. MethodsUsing femtosecond pulse lasers, we prepare delayed and phase-adjustable pairs of femtosecond pulses. These modulated pulse pairs excite fluorescent single molecules labeled within cells through a microscopic system, followed by the collection and recording of the arrival time of each fluorescent photon. By defining the quantum coherence visibility (V) of single molecules in relation to the surrounding environmental temperature, a correspondence between V and environmental temperature is established. By modulating and demodulating the arrival times of fluorescent photons, we obtain the local temperature of single molecules. Combined with scanning imaging, we finally achieve temperature imaging and real-time detection of cells. ResultsThis method achieves high precision (temperature resolution<0.1°C) and a wide temperature range (10-50°C) for temperature imaging and measurement, and it enables the observation of temperature changes related to individual cell metabolism. ConclusionThis research contributes to a deeper understanding of cellular metabolism, protein function, and disease mechanisms, providing a valuable tool for biomedical research.

ObjectiveTemporal heterogeneity in lung cancer presents as fluctuations in the biological characteristics, genomic mutations, proliferation rates, and chemotherapeutic responses of tumor cells over time, posing a significant barrier to effective treatment. The complexity of this temporal variance, coupled with the spatial diversity of lung cancer, presents formidable challenges for research. This article will pave the way for new avenues in lung cancer research, aiding in a deeper understanding of the temporal heterogeneity of lung cancer, thereby enhancing the cure rate for lung cancer. MethodsRaman spectroscopy emerges as a powerful tool for real-time surveillance of biomolecular composition changes in lung cancer at the cellular scale, thus shedding light on the disease’s temporal heterogeneity. In our investigation, we harnessed Raman spectroscopic microscopy alongside multivariate statistical analysis to scrutinize the biomolecular alterations in human lung epithelial cells across various timeframes after benzo(a)pyrene exposure. ResultsOur findings indicated a temporal reduction in nucleic acids, lipids, proteins, and carotenoids, coinciding with a rise in glucose concentration. These patterns suggest that benzo(a)pyrene induces structural damage to the genetic material, accelerates lipid peroxidation, disrupts protein metabolism, curtails carotenoid production, and alters glucose metabolic pathways. Employing Raman spectroscopy enabled us to monitor the biomolecular dynamics within lung cancer cells in a real-time, non-invasive, and non-destructive manner, facilitating the elucidation of pivotal molecular features. ConclusionThis research enhances the comprehension of lung cancer progression and supports the development of personalized therapeutic approaches, which may improve the clinical outcomes for patients.