Objective To evaluate the role of distortion product otoacoustic emissions (DPOAE) testing in evaluating early hearing loss among noise-exposed workers. Methods A total of 174 noise-exposed workers in a metal shipbuilding enterprise were selected as the research subjects by the convenience sampling method. Pure tone audiometry (PTA), DPOAE and the level of noise exposure were conducted on the workers. The rank correlation analysis was used to analyze the correlation between DPOAE amplitude and PTA threshold. The multilevel model was used to analyze the effects of gender, age, noise exposure intensity, cumulative noise exposure (CNE), hearing loss classification and PTA threshold on DPOAE results. Results At the frequencies of 0.50, 1.00, 2.00, 3.00, 4.00, 6.00 and 8.00 kHz, the DPOAE amplitude was negatively correlated with the PTA threshold (rank correlation coefficients were -0.12, -0.48, -0.47, -0.18, -0.23, -0.44, -0.19, respectively, all P<0.01). At the most frequencies, DPOAE amplitude was negatively correlated with age and CNE (all P<0.05). The results of multilevel model analysis showed that there were significant differences in DPOAE amplitudes at certain frequencies across gender, age, noise intensity, CNE, and hearing loss classification (all P<0.05). Significant differences in DPOAE responses were found among different CNE and hearing loss groups (all P<0.01). Conclusion DPOAE testing can objectively reflect the hearing status of noise-exposed workers and could be considered for inclusion in routine hearing monitoring to facilitate early detection of noise-induced hearing loss.

ObjectiveTo optimize Tusizi prescription for ovarian reserve function based on the uniform design method combined with in vitro experiments and explore the underlying mechanisms of this prescription. MethodsThe uniform design method was adopted to design a 5-factor 11-level experiment on the water extract of Tusizi prescription. The cell-counting kit-8 （CCK-8） assay was employed to measure the viability of human ovarian granulosa cells （KGN cells） treated with Tusizi prescription extracts 1-11， and multivariate regression analysis was performed to determine the optimal herb ratio in this prescription. The potential targets of active ingredients in the prescription were retrieved from traditional Chinese medicine systems pharmacology database and analysis platform （TCMSP） and encyclopedia of traditional Chinese medicine （ETCM）. The common targets shared by Tusizi prescription and diminished ovarian reserve （DOR） were selected and imported into search tool for the retrieval of interacting genes/proteins （STRING） to construct a protein-protein interaction （PPI） network and into gene function annotation database （DAVID） for gene ontology （GO） analysis. The CCK-8 assay was used to measure the viability of ovarian germline stem cells treated with hyperoside. The CCK-8 assay， 5-ethynyl-2'-deoxyuridine （EdU） staining， terminal-deoxynucleoitidyl transferase mediated nick-end labeling （TUNEL）， and enzyme-linked immunosorbent assay （ELISA） were employed to examine the proliferation， apoptosis， and estradiol （E₂） secretion of KGN cells treated with the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design. On this basis， the optimal prescription composition for maximizing the effect on ovarian reserve function was determined and preliminary insights into the underlying mechanisms of this prescription were gained. ResultsA total of 147 common targets were obtained from 278 targets of Tusizi prescription and 1 721 targets of DOR. GO analysis revealed 194 biological processes， primarily involving cellular responses to exogenous compound stimuli， negative regulation of apoptotic process， and positive regulation of cell proliferation. It identified 84 cellular components， including cell membrane， mitochondria， and neuronal cell body， as well as 144 molecular functions such as enzyme binding， estrogen response element binding， and nuclear estrogen receptor binding. The multivariate regression analysis revealed that when Tusizi prescription was composed of Cuscutae Semen， Lycii Fructus， Dioscoreae Rhizoma， Poria， and Nelumbinis Semen in a ratio of 27∶30∶17∶12∶14， the water extract of Tusizi prescription had the best effect of enhancing the viability of KGN cells. CCK-8 results showed that compared with the normal group， the hyperoside group demonstrated increased viability of ovarian germline stem cells （P<0.01）. The CCK-8， EdU， and ELISA results showed that compared with the normal group， the optimal prescription screened by uniform design and the water extract 11 of Tusizi prescription increased the proliferation and reduced the apoptosis of KGN cells （P<0.05， P<0.01）. ELISA results showed that compared with the normal group， the water extract 11 of Tusizi prescription promoted the E₂ secretion of KGN cells （P<0.05）， while the optimal prescription screened by uniform design had no significant effect on the E₂ secretion. ConclusionBoth the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 27∶30∶17∶12∶14） can improve the ovarian reserve function， and the former has better effect. Tusizi prescription can modulate biological processes （such as cell proliferation and apoptosis） and molecular functions （such as enzyme binding and estrogen response element binding） through active components like hyperoside to promote the proliferation and E₂ secretion and inhibit the apoptosis of KGN cells， thereby protecting the ovarian reserve function.

ObjectiveTo optimize Tusizi prescription for ovarian reserve function based on the uniform design method combined with in vitro experiments and explore the underlying mechanisms of this prescription. MethodsThe uniform design method was adopted to design a 5-factor 11-level experiment on the water extract of Tusizi prescription. The cell-counting kit-8 （CCK-8） assay was employed to measure the viability of human ovarian granulosa cells （KGN cells） treated with Tusizi prescription extracts 1-11， and multivariate regression analysis was performed to determine the optimal herb ratio in this prescription. The potential targets of active ingredients in the prescription were retrieved from traditional Chinese medicine systems pharmacology database and analysis platform （TCMSP） and encyclopedia of traditional Chinese medicine （ETCM）. The common targets shared by Tusizi prescription and diminished ovarian reserve （DOR） were selected and imported into search tool for the retrieval of interacting genes/proteins （STRING） to construct a protein-protein interaction （PPI） network and into gene function annotation database （DAVID） for gene ontology （GO） analysis. The CCK-8 assay was used to measure the viability of ovarian germline stem cells treated with hyperoside. The CCK-8 assay， 5-ethynyl-2'-deoxyuridine （EdU） staining， terminal-deoxynucleoitidyl transferase mediated nick-end labeling （TUNEL）， and enzyme-linked immunosorbent assay （ELISA） were employed to examine the proliferation， apoptosis， and estradiol （E₂） secretion of KGN cells treated with the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design. On this basis， the optimal prescription composition for maximizing the effect on ovarian reserve function was determined and preliminary insights into the underlying mechanisms of this prescription were gained. ResultsA total of 147 common targets were obtained from 278 targets of Tusizi prescription and 1 721 targets of DOR. GO analysis revealed 194 biological processes， primarily involving cellular responses to exogenous compound stimuli， negative regulation of apoptotic process， and positive regulation of cell proliferation. It identified 84 cellular components， including cell membrane， mitochondria， and neuronal cell body， as well as 144 molecular functions such as enzyme binding， estrogen response element binding， and nuclear estrogen receptor binding. The multivariate regression analysis revealed that when Tusizi prescription was composed of Cuscutae Semen， Lycii Fructus， Dioscoreae Rhizoma， Poria， and Nelumbinis Semen in a ratio of 27∶30∶17∶12∶14， the water extract of Tusizi prescription had the best effect of enhancing the viability of KGN cells. CCK-8 results showed that compared with the normal group， the hyperoside group demonstrated increased viability of ovarian germline stem cells （P<0.01）. The CCK-8， EdU， and ELISA results showed that compared with the normal group， the optimal prescription screened by uniform design and the water extract 11 of Tusizi prescription increased the proliferation and reduced the apoptosis of KGN cells （P<0.05， P<0.01）. ELISA results showed that compared with the normal group， the water extract 11 of Tusizi prescription promoted the E₂ secretion of KGN cells （P<0.05）， while the optimal prescription screened by uniform design had no significant effect on the E₂ secretion. ConclusionBoth the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 27∶30∶17∶12∶14） can improve the ovarian reserve function， and the former has better effect. Tusizi prescription can modulate biological processes （such as cell proliferation and apoptosis） and molecular functions （such as enzyme binding and estrogen response element binding） through active components like hyperoside to promote the proliferation and E₂ secretion and inhibit the apoptosis of KGN cells， thereby protecting the ovarian reserve function.

ObjectiveTo explore the effect of serum containing Zhenwutang on myocardial mast cell apoptosis induced by angiotensin Ⅱ （AngⅡ） and the mechanism of the correlation between apoptosis and mitochondrial autophagy. MethodsIn this experiment， AngⅡ and serum containing Zhenwutang with different concentrations were used to interfere with H9C2 cardiomyocytes for 24 h， and the survival rate of H9C2 cardiomyocytes was detected by cell counting kit-8 （CCK-8） to screen the optimal concentration for the experiment. Enzyme-linked immunosorbent assay （ELISA） was used to detect the content of B-type natriuretic peptide （BNP） in cell culture supernatant， and immunofluorescence was used to detect the cell surface area to verify the construction of the myocardial mast cell model. Subsequently， the experiment was divided into a blank group （20% blank serum）， a model group （20% blank serum + 5×10^-5 mol·L^-1 AngⅡ）， low-， medium-， and high-dose （5%， 10% and 20%） serum containing Zhenwutang groups， an autophagy inhibitor group （1×10^-4 mol·L^-1 3-MA）， and autophagy inducer group （1×10^-7 mol·L^-1 rapamycin）. The apoptosis level of H9C2 cells and the changes of mitochondrial membrane potential were detected by flow cytometry. The lysosomal probe （Lyso Tracker） and mitochondrial probe （Mito Tracker） co-localization was employed to detect autophagy. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect Caspase-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， Bcl-2-related X protein （Bax）， and cytochrome C （Cyt C） in apoptosis-related pathways and the relative mRNA expression of ubiquitin ligase （Parkin）， phosphatase and tensin homolog （PTEN）-induced kinase 1 （PINK1）， and p62 protein in mitochondrial autophagy-related pathways. Western blot was used to detect cleaved Caspase-3， cleaved Caspase-9， Bax， Bcl-2， and Cyt C in apoptosis-related pathways， phosphorylated ubiquitin ligase （p-Parkin）， phosphorylated PTEN-induced kinase 1 （p-PINK1）， p62， and Bcl-2 homology domain protein Beclin1 in mitochondrial autophagy-related pathways， and the change of microtubule-associated protein 1 light chain 3 （LC3） Ⅱ/Ⅰ ratio. ResultsCCK-8 showed that when the concentration of AngⅡ was 5×10^-5 mol·L^-1， the cell activity was the lowest， and there was no cytotoxicity. At this concentration， the surface area of cardiomyocytes was significantly increased （P<0.01）， and the content of BNP in the supernatant of culture medium was significantly increased （P<0.05）. Therefore， AngⅡ with a concentration of 5×10^-5 mol·L^-1 was selected for the subsequent modeling of myocardial mast cells. Compared with the blank group， the model group and the autophagy inhibitor 3-MA group had a significantly increased apoptosis rate （P<0.01） and significantly decreased mitochondrial membrane potential （P<0.01）. The results of immunofluorescence co-localization showed that compared with the blank group， the model group had a significantly decreased number of red and green fluorescence spots. The results of Real-time PCR showed that compared with that in the blank group， the relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 in the model group was significantly up-regulated （P<0.01）， while the relative mRNA expression of Bcl-2， Parkin， and PINK1 was significantly down-regulated （P<0.01）. In addition， the relative protein expression of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 was significantly up-regulated （P<0.01）. The LC3Ⅱ/Ⅰ was significantly decreased， and the relative protein expression of Bcl-2， p-Parkin， p-PINK1， and Beclin1 was significantly down-regulated （P<0.01）. Compared with the model group， the serum containing Zhenwutang groups and the autophagy inducer group had significantly decreased apoptosis rate （P<0.01）， and the decrease ratio of mitochondrial membrane potential is significantly lowered （P<0.01） in a dose-dependent manner. Additionally， both red and green fluorescence spots became more in these groups. In the 3-MA group， the number of red and green fluorescence spots decreased significantly. The relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 was significantly down-regulated （P<0.05， P<0.01）， while that of Bcl-2， Parkin， and PINK1 was significantly up-regulated （P<0.01）. In the serum containing Zhenwutang groups， the relative protein expression levels of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 were significantly down-regulated （P<0.05，P<0.01）. The LC3Ⅱ/Ⅰ was significantly increased， and the relative protein expression levels of Bcl-2， p-Parkin， p-PINK1， and Beclin1 were significantly up-regulated （P<0.01）. ConclusionThe serum containing Zhenwutang can reduce the apoptosis of myocardial mast cells and increase mitochondrial autophagy. This is related to the inhibition of intracellular Bax/Bcl-2/Caspase-3 apoptosis pathway and regulation of Parkin/PINK1 mitochondrial autophagy pathway.

Objective To investigate the preventive effects of lidocaine administered through different routes on cardiovascular stress responses during anesthesia tracheal intubation. Methods Total 120 patients scheduled for elective surgery under general anesthesia were randomly divided into three groups: intravenous injection group （group IV）, throat spray group （group LJ）, and control group （group CT）, with 40 patients in each. Group IV received 50 mg of lidocaine via intravenous injection 1 minute before tracheal intubation. Group LJ received 50 mg of lidocaine sprayed into the pharyngeal cavity, glottis, and subglottic area. Group CT did not receive any treatment, and the remaining procedures were performed following the routine general anesthesia induction protocol. Heart rate （HR）, systolic blood pressure （SBP）, diastolic blood pressure （DBP）, and mean arterial pressure （MAP） were recorded at four time points: T₀ （before tracheal intubation）, T₁ （immediately after tracheal intubation）, T₂ （3 minutes after intubation）, and T₃ （5 minutes after intubation）. Statistical analysis of the data was performed using SPSS 22.0. Results There were no significant differences in HR at various time points within the group LJ. The changes in HR in the group IV and group CT were different statistically from those in the throat spray group. The blood pressure of patients in all three groups increased to varying degrees immediately after tracheal intubation, with the group CT showing particularly significant changes that differed significantly from both the group IV and the group LJ. The group LJ rapidly returned to levels close to those before intubation. Conclusion The preventive effects of lidocaine on stress responses during tracheal intubation were different depending on the route of administration. The inhibitory preventive effect of the throat spray method was superior to that of intravenous lidocaine, especially in preventing changes in heart rate.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

ObjectiveRepetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease (AD), but the neurobiological mechanisms linking synaptic pathology, neural oscillatory dynamics, and brain network reorganization remain unclear. This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments, molecular profiling, and neurophysiological monitoring. MethodsIn this prospective double-blind trial, 12 AD patients underwent a 14-day protocol of 20 Hz rTMS, with comprehensive multimodal assessments performed pre- and post-intervention. Cognitive functioning was quantified using the mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA), while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living (ADL) scale and combined neuropsychiatric inventory (NPI)-Hamilton depression rating scale (HAMD). Peripheral blood biomarkers, specifically Aβ1-40 and phosphorylated tau (p-tau181), were analyzed to investigate the effects of rTMS on molecular metabolism. Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients, while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization. Furthermore, systematic assessment of correlations between cognitive scale scores, blood biomarkers, and network characteristics was performed to elucidate cross-modal therapeutic associations. ResultsClinically, MMSE and MOCA scores improved significantly (P<0.05). Biomarker showed that Aβ1-40 level increased (P<0.05), contrasting with p-tau181 reduction. Moreover, the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores. Post-intervention analyses revealed significant modulations in oscillatory power, characterized by pronounced reductions in delta (P<0.05) and theta bands (P<0.05), while concurrent enhancements were observed in alpha, beta, and gamma band activities (all P<0.05). Network analysis revealed frequency-specific reorganization: clustering coefficients were significantly decreased in delta, theta, and alpha bands (P<0.05), while global efficiency improvement was exclusively detected in the delta band (P<0.05). The alpha band demonstrated concurrent increases in average nodal degree (P<0.05) and characteristic path length reduction (P<0.05). Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181. Additionally, the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band. However, the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands. Conclusion20 Hz rTMS targeting dorsolateral prefrontal cortex (DLPFC) significantly improves cognitive function and enhances the metabolic clearance of β-amyloid and tau proteins in AD patients. This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation, which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks. These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales, blood biomarkers, and EEG——in understanding and monitoring the progression of AD. This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.

Nuclear emergency medical rescue is one of the important courses of military medical professional education, and improving the training level of nuclear emergency medical rescue plays a very important role in improving post competency of trainees. Based on the problem of disconnection between "teaching" and "need" in the occupational education of nuclear emergency medical rescue in the past, this study proposes the curriculum goal of "the combination of three abilities" and performs the optimization and practice of the occupational education curriculum system of nuclear emergency medical rescue from the aspects of curriculum setting, curriculum content, teaching methods, and assessment and evaluation. The results show that the new curriculum system can significantly improve the comprehensive ability of nuclear emergency medical rescue among trainees and better meet the requirements for their posts, thereby playing an important role in cultivating high-quality military medical talents in nuclear emergency medical rescue.

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.

Heart failure with preserved ejection fraction(HFpEF)is a highly heterogeneous systemic condition and represents the predominant form of heart heart failure(HF)worldwide.Current pharmacotherapies for HFpEF are limited and lack specific targeted drugs.Recent studies suggest that non-pharmacological strategies serve as adjuncts to conventional pharmacological treatment,offering improvements in symptoms,quality of life,and reducing the risk of rehospitalization for HF in patients with HFpEF.These strategies include CD34 stem cell transplantation,the greater splanchnic nerve ablation,atrial septal shunting,atrial pacing,myocardial contractility modulation,left ventricular expander,baroreceptor stimulation,and others.This review comprehensively summarizes the latest clinical evidence on non-pharmacological treatments for HFpEF,with the aim of advancing the understanding of treatment strategies for this condition.