Objective To quantify the volume and movement of cardiac substructures by using coronary computed tomography angiography(CCTA)to provide guidance for the design of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.Methods Totally 18 female patients who received conventional chest plain scan and CCTA were selected to simulate the design process of radiotherapy plan for left breast cancer patients with internal mammary lymph nodes.Retrospective reconstruction of CCTA data was performed for each patient,with 10 phase images(with an interval of 10％)within a R-R cardiac cycle(10％-100％)to simulate the true range of motion of the heart.The heart,left atrium(LA),left ventricle(LV),right atrium(RA),right ventricle(RV),left anterior descending artery(LAD),left circumflex coronary artery(LCX)and right coronary artery(RCA)were contoured at each phase.The distances from the centroid position to the average position of LAD,LCX and RCA were measured at each phase in the superior-inferior(SI),anterior-posterior(AP)and left-right(LR).The average volume and range of volume changes of LA,LV,RA,RV and heart were analyzed within a cardiac cycle.The expansion margins of planning organs at risk volume(PRV)were calculated.SPSS 19.0 software was used for statistical analysis.Results The following average absolute displacements were found in SI,AP and LR coordinates:(1.8±0.7)mm,(1.2±0.5)mm and(1.5±0.5)mm for LAD,respectively;(2.1±0.7)mm,(1.5±0.6)mm and(1.9±0.7)mm for LCX,respectively;(1.6±0.5)mm,(2.2±0.9)mm and(2.2±0.8)mm for RCA,respectively.The volume changes of LA,LV,RA,RV and heart within a cardiac cycle ranged from 34.3 to 63.9 cm3,122.1 to 154.3 cm3,29.3 to 53.6 cm3,57.2 to 94.3 cm3 and 480.1 to 515.4 cm3,respectively.The theoretical expansion margins of LAD,LCX and RCA in all the three directions were within 2 mm.Conclusion The ranges of movement and volume changes of cardiac substructure are quantitati-vely displayed,and references are provided for the planning of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.[Chinese Medical Equipment Journal,2025,46(3):54-58]

To establish a method for detecting Toxoplasma gondii based on recombinant polymerase amplification(RPA)technology and apply it to clinical sample validation of pet cats.Using the 529 repeat sequence of the Toxoplasma gondii gene as the target gene sequence,primers and probes were designed,and the Rep-529 recombinant plasmid was constructed as the standard.A fluorescent RPA reaction system was established.Dilute the plasmid standard 10 times to different concentrations as the detection template for sensitivity testing;Specific testing was conducted using genomic DNA from several parasitic spe-cies,including Toxoplasma gondii,Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia flagellata,Babesia bo-vis and Theileria annulata as templates;Simultaneously,fluorescence RPA and RT-PCR were used to detect 52 positive and 40 negative cats clinical samples,and the coincidence rate of the detection results of the two methods were compared and ana-lyzed.The RPA reaction system was successfully established using PTRep recombinant plasmid as the standard,ToxD-F/ToxD-R as the primer,and RepD-P as the fluorescent probe.The reaction temperature was constant at 39 ℃,the reaction time was 30 minutes,and the detection sensitivity was 1 copy/μL.There is no significant cross reaction with parasites such as Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia,Babesia bovis and Theileria annulata,and the specificity is good.A total of 92 clinical fecal samples from cats were tested,and the positive coincidence rate of fluorescence RPA detection method was higher than that of conventional RT-PCR method(98.08％vs.82.69％),and the difference of the positive rate was not statistically significant(X2=1.392,P＞0.05).The fluorescence RPA detection method for Toxoplasma gondii suc-cessfully established in this study has the characteristics of being fast,sensitive,specific,accurate,and reliable.It can be used as a rapid clinical detection kit for Toxoplasma gondii in cats and other animals,providing new technical support for the subsequent epidemiological monitoring and precise clinical diagnosis of toxoplasmosis in cats,other animals,and humans in the future.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Aim To explore the mechanism of Yangxin decoction in the treatment of chronic heart failure(CHF)based on network pharmacology and animal ex-periments.Methods The database was used to screen Yangxin decoction,a network of"drug-compo-nent-disease-target"was established,and the obtained targets were enriched and analyzed.The CHF model of rats was replicated by abdominal aortic ligation.After the administration,the general condition,body weight and heart weight of the rats were observed,and the he-modynamic changes,echocardiography indicators and left ventricular mass index were measured.HE staining was used to observe the morphological changes of myo-cardial tissue.Serum IL-1 β,IL-18,TNF-α and BNP were detected by ELISA.The expressions of NLRP3,caspase-1,ASC and NF-κB p65 proteinswere detected by Western blot.Results Enrichment analysis showed that the potential regulatory pathways of Yangx-in decoction in the treatment of CHF involved NOD-like signaling pathway,NF-κB signaling pathway,etc.The results of animal experiments showed that the body weight,left ventricular diastolic diameter and left ven-tricular systolic diameter of the rats in the administra-tion group decreased(P＜0.05),the left ventricular mass index,ejection fraction and short axis narrowing rate increased(P＜0.05),the pathological morphology of myocardial tissue was reduced,and the levels of IL-1 β,IL-18,TNF-α,BNP,NLRP3,caspase-1,ASC and NF-κB p65 decreased(P＜0.05).Conclusions The mechanism of Yangxin decoction in the treatment of CHF rats may be related to inhibiting the activation of NLRP3 inflammasome signaling pathway and reduc-ing the inflammatory response.

Aim To explore the mechanism of Yangxin decoction in the treatment of chronic heart failure(CHF)based on network pharmacology and animal ex-periments.Methods The database was used to screen Yangxin decoction,a network of"drug-compo-nent-disease-target"was established,and the obtained targets were enriched and analyzed.The CHF model of rats was replicated by abdominal aortic ligation.After the administration,the general condition,body weight and heart weight of the rats were observed,and the he-modynamic changes,echocardiography indicators and left ventricular mass index were measured.HE staining was used to observe the morphological changes of myo-cardial tissue.Serum IL-1 β,IL-18,TNF-α and BNP were detected by ELISA.The expressions of NLRP3,caspase-1,ASC and NF-κB p65 proteinswere detected by Western blot.Results Enrichment analysis showed that the potential regulatory pathways of Yangx-in decoction in the treatment of CHF involved NOD-like signaling pathway,NF-κB signaling pathway,etc.The results of animal experiments showed that the body weight,left ventricular diastolic diameter and left ven-tricular systolic diameter of the rats in the administra-tion group decreased(P＜0.05),the left ventricular mass index,ejection fraction and short axis narrowing rate increased(P＜0.05),the pathological morphology of myocardial tissue was reduced,and the levels of IL-1 β,IL-18,TNF-α,BNP,NLRP3,caspase-1,ASC and NF-κB p65 decreased(P＜0.05).Conclusions The mechanism of Yangxin decoction in the treatment of CHF rats may be related to inhibiting the activation of NLRP3 inflammasome signaling pathway and reduc-ing the inflammatory response.

Objective To quantify the volume and movement of cardiac substructures by using coronary computed tomography angiography(CCTA)to provide guidance for the design of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.Methods Totally 18 female patients who received conventional chest plain scan and CCTA were selected to simulate the design process of radiotherapy plan for left breast cancer patients with internal mammary lymph nodes.Retrospective reconstruction of CCTA data was performed for each patient,with 10 phase images(with an interval of 10％)within a R-R cardiac cycle(10％-100％)to simulate the true range of motion of the heart.The heart,left atrium(LA),left ventricle(LV),right atrium(RA),right ventricle(RV),left anterior descending artery(LAD),left circumflex coronary artery(LCX)and right coronary artery(RCA)were contoured at each phase.The distances from the centroid position to the average position of LAD,LCX and RCA were measured at each phase in the superior-inferior(SI),anterior-posterior(AP)and left-right(LR).The average volume and range of volume changes of LA,LV,RA,RV and heart were analyzed within a cardiac cycle.The expansion margins of planning organs at risk volume(PRV)were calculated.SPSS 19.0 software was used for statistical analysis.Results The following average absolute displacements were found in SI,AP and LR coordinates:(1.8±0.7)mm,(1.2±0.5)mm and(1.5±0.5)mm for LAD,respectively;(2.1±0.7)mm,(1.5±0.6)mm and(1.9±0.7)mm for LCX,respectively;(1.6±0.5)mm,(2.2±0.9)mm and(2.2±0.8)mm for RCA,respectively.The volume changes of LA,LV,RA,RV and heart within a cardiac cycle ranged from 34.3 to 63.9 cm3,122.1 to 154.3 cm3,29.3 to 53.6 cm3,57.2 to 94.3 cm3 and 480.1 to 515.4 cm3,respectively.The theoretical expansion margins of LAD,LCX and RCA in all the three directions were within 2 mm.Conclusion The ranges of movement and volume changes of cardiac substructure are quantitati-vely displayed,and references are provided for the planning of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.[Chinese Medical Equipment Journal,2025,46(3):54-58]

To establish a method for detecting Toxoplasma gondii based on recombinant polymerase amplification(RPA)technology and apply it to clinical sample validation of pet cats.Using the 529 repeat sequence of the Toxoplasma gondii gene as the target gene sequence,primers and probes were designed,and the Rep-529 recombinant plasmid was constructed as the standard.A fluorescent RPA reaction system was established.Dilute the plasmid standard 10 times to different concentrations as the detection template for sensitivity testing;Specific testing was conducted using genomic DNA from several parasitic spe-cies,including Toxoplasma gondii,Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia flagellata,Babesia bo-vis and Theileria annulata as templates;Simultaneously,fluorescence RPA and RT-PCR were used to detect 52 positive and 40 negative cats clinical samples,and the coincidence rate of the detection results of the two methods were compared and ana-lyzed.The RPA reaction system was successfully established using PTRep recombinant plasmid as the standard,ToxD-F/ToxD-R as the primer,and RepD-P as the fluorescent probe.The reaction temperature was constant at 39 ℃,the reaction time was 30 minutes,and the detection sensitivity was 1 copy/μL.There is no significant cross reaction with parasites such as Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia,Babesia bovis and Theileria annulata,and the specificity is good.A total of 92 clinical fecal samples from cats were tested,and the positive coincidence rate of fluorescence RPA detection method was higher than that of conventional RT-PCR method(98.08％vs.82.69％),and the difference of the positive rate was not statistically significant(X2=1.392,P＞0.05).The fluorescence RPA detection method for Toxoplasma gondii suc-cessfully established in this study has the characteristics of being fast,sensitive,specific,accurate,and reliable.It can be used as a rapid clinical detection kit for Toxoplasma gondii in cats and other animals,providing new technical support for the subsequent epidemiological monitoring and precise clinical diagnosis of toxoplasmosis in cats,other animals,and humans in the future.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Tumors continue to be a major challenge in human survival that we have yet to overcome. Despite the variety of treatment options available, we have not yet found an effective method. As more and more research is conducted, attention has been turned to a new field for tumor treatment—the tumor microenvironment (TME). This is a dynamic and complex environment consisting of various matrix cells surrounding cancer cells, including surrounding immune cells, blood vessels, extracellular matrix, fibroblasts, bone marrow-derived inflammatory cells, signaling molecules, and some specific cell types. Firstly, endothelial cells play a key role in tumor development and the immune system’s protection of tumor cells. Secondly, immune cells, such as macrophages, Treg cells, Th17 cells, are widely involved in various immune responses and activities in the human body, such as inflammation responses promoting survival carefully orchestrated by the tumor. Even though many studies have extensively researched the TME and found many research schemes, so far, no key effective method has been found to treat tumors by affecting the TME. The TME is a key interaction area between the host immune system and the tumor. Cells within the TME influence each other and interact with cancer cells to affect cancer cell invasion, tumor growth, and metastasis. This is a new direction for cancer treatment. In the complex environment of the TME, post-translational modifications (PTMs) of proteins have been proven to play an important role in the TME. PTMs are dynamic, strictly regulated changes to proteins that control their function by regulating their structure, spatial location, and interaction. Among PTMs, a reversible post-translational modification called SUMOylation is a common regulatory mechanism in cellular processes. It is a post-translational modification that targets lysine residues with a small ubiquitin-like modifier (SUMO) in a reversible post-translational modification manner. SUMOylation is widely involved in carcinogenesis, DNA damage response, cancer cell proliferation, metastasis, and apoptosis, playing a pivotal role in the TME, such as DNA damage repair, tumor metastasis, and also participates in immune cell differentiation, activation, and inhibition of immune cells. On the other hand, SUMO or sentrin-specific protease (SENP) inhibitors can interfere with the SUMOylation process, thereby affecting many biological processes, including immune response, carcinogenesis, cell cycle progression, and cell apoptosis, etc. In summary, this review aims to introduce the dynamic modification of protein SUMOylation on various immune cells and the application of various inhibitors, thereby exploring its role in the TME. This is a challenging but hopeful field, and we look forward to future research that can bring more breakthroughs. In conclusion, the TME is a complex and dynamic environment that plays a crucial role in the development and progression of tumors. Understanding the intricate interactions within the TME and the role of PTMs, particularly SUMOylation, could provide valuable insights into the mechanisms of tumor development and potentially lead to the development of novel therapeutic strategies. The study of SUMOylation and its effects on various immune cells in the TME is an exciting and promising area of research that could significantly advance our understanding of tumor biology and potentially lead to the development of more effective treatments for cancer. This is a challenging but hopeful field, and we look forward to future research that can bring more breakthroughs.