Objective:To establish a serum detection method of surface-enhanced Raman spectroscopy (SERS) combining with machine learning for early screening of colorectal cancer (CRC).Methods:Serum samples were collected from 150 CRC patients diagnosed at Jiangdu People′s Hospital, Affiliated to Yangzhou University, and also from 37 healthy subjects. Gold nanohexapod (AuNHs) arrays were prepared using an oil-water interface self-assembly method. A 5 μl serum sample was applied onto the AuNHs array. Scatheless and rapid detection for serum were performed using a Renishaw inVia Raman spectrometer at room temperature with a laser wavelength of 785 nm, exposure time of 10 s, and power of 5 mW. The raw SERS spectra were preprocessed using Savitzky-Golay smoothing, AsLS baseline correction, and Min-Max normalization with Origin 2019 software. Furthermore, the principal component analysis (PCA)-support vector machine (SVM) model was constructed using Python′s scikit-learn library. Leave-One-Out Cross-Validation (LOOCV) was used to evaluate the model′s accuracy, sensitivity, specificity, and area under the curve (AUC).Results:The AuNHs arrays exhibited uniform morphology. The relative standard deviation (RSD) of the SERS intensity at 1 080 cm -1 was 5.69%, and the RSD of the SERS intensity at 1 340 cm -1 was 6.20%. The limit of detection (LOD) of the AuNHs array was 9.42×10 -12 mol/L. The PCA-SVM model achieved an accuracy of 90.91% (170/187), sensitivity of 96.79% (181/187), specificity of 99.47% (186/187), and an AUC of 0.98. The most significant characteristic peaks distinguishing different CRC stages were at 747, 940, 1 000, 1 447, and 1 612 cm -1. Conclusion:The serum detection method based on SERS combined with machine learning can accurately screen CRC with higher accuracy, sensitivity, and specificity, demonstrating potential clinical application value.

Objective To investigate the current situation of off-label use of immune checkpoint inhibitors(ICIs)in China and the cognition of medical staff.Methods From August 31 to September 9,2022,a nationwide survey questionnaire was sent to medical staff in the form of electronic questionnaire.The questionnaire included 13 questions,covering four dimensions:Drug allocation,current situation of medication beyond the instructions,cognition of medication beyond the instructions and current situation of medication beyond the instructions.Results A total of 745 questionnaires were collected.75.70％of respondents reported off-label use of ICIs in their hospitals,with the most common type being off-label indications.The primary reasons for such practices included support from authoritative domestic and international guidelines,clinical research data validation,and approved indications in foreign regulatory documents.85.37％of respondents believed off-label use could offer new hope for patients,while 68.86％considered it unlikely to increase adverse reactions.44.97％of respondents' hospitals had not established off-label use registration systems for ICIs.88.86％of respondents emphasized the need for stricter regulations governing off-label use of immunotherapeutic agents.Conclusion Off-label use of ICIs is common,and there is a lack of unified guidance in clinical practice.It is urgent to form norms and consensus on the management of off-label use of ICIs.

Objective To investigate the relationship between cystatin C(CysC)/prealbumin(PAB)ratio and lung function and chronic obstructive pulmonary disease(COPD)assessment test(CAT)score in patients with COPD.Methods A total of 216 COPD patients admitted to the hospital from February 2021 to February 2024 were selected as the study group,and 150 healthy subjects were selected as the control group during the same period.CysC and PAB levels were detected by immunoturbidimetry,CysC/PAB ratio was calculated,lung function was detected and CAT scores were recorded.Pearson correlation was used to analyze the rela-tionship between CysC/PAB ratio,lung function and CAT score in COPD patients.Results The CysC and CysC/PAB ratio in the study group was significantly higher than that in the control group,and the level of PAB was significantly lower than that in the control group,with statistical significance(P＜0.05).The forced expiratory volume in the first second as a percentage of predicted value(FEV1％pred),the percentage of pre-dicted forced vital capacity(FVC％pred)and the ratio of the first second forced expiratory volume to forced vital capacity(FEV1/FVC)of the study group were lower than those of the control group,and the CAT score of the study group was higher than that of the control group,with statistical significance(P＜0.05).The Cy-sC/PAB ratio and CAT score of COPD patients with the global initiative for chronic obstructive lung disease(GOLD)grade 4 were significantly higher than those with GOLD grade 3,GOLD grade 2 and GOLD grade 1,and the difference was statistically significant(P＜0.05).The ratio of CysC/PAB in very severely affected pa-tients was higher than that in severely affected,moderately affected and mildly affected patients,while the ra-tio of FEV1％pred,FVC％pred and FEV1/FVC was lower than that in severely affected,moderately affected and mildly affected patients,and the difference was statistically significant(P＜0.05).In COPD patients,Cy-sC/PAB ratio was negatively correlated with FEV1％pred,FVC％pred,FEV1/FVC,and positively correlated with CAT score(P＜0.05).Conclusion CysC/PAB ratio is highly expressed in COPD patients,and its level is related to lung function and CAT score,which can reflect the degree of disease and quality of life in COPD patients to a certain extent.

This study investigated the prevalence and potential mechanisms of gentamicin heterore-sistance in Streptococcus isolates from dairy cows.In this study,A total of 39 Streptococcus isola-ted from raw milk were collected,and the minimum inhibitory concentration(MIC)of gentamicin and other drugs on the isolates was determined by micro broth dilution method,and the K-B paper diffusion method,colony analysis profile(PAP),and resistance stability test were used to investigate the heteroresistance characteristics of Streptococcus,and the mechanism of heteroresis-tance was analyzed based on whole genome sequencing and resequencing.Seven suspected heterore-sistance strains were identified by K-B paper diffusion method,accounting for 17.95％(7/39)of the total number of suspected strains.PAP confirmed that the MIC to MNIC ratio of L147,L108 and L174 was greater than 8,and the frequency of resistant subgroups ranged from 1.38×10-5 to 8.18 × 10-5,which was greater than 1 × 10-7,confirming that they were heteroresistance strains.Resistance stability tests revealed that the resistant subpopulations of all three strains were not stably inherited.Whole-genome sequencing revealed mutations in the ribosomal target genes of aminoglycoside antibiotics,rsmA,rsmB and rsmE,compared with the reference genome,which may lead to heteroresistance to gentamicin in Streptococcus.The occurrence of heteroresistance of Streptococcus to gentamicin is high in dairy sources,so more attention should be paid to the occur-rence of heteroresistance when using gentamicin for clinical treatment.

Objective To observe the value of dynamic attention aggregation network(DAANet)for automatic segmentation of anomalous origin of the left coronary artery from the pulmonary artery(ALCAPA)in CT angiography(CTA).Methods CTA data in 30 patients with ALCAPA syndrome were retrospectively enrolled.ALCAPA were segmented in CTA with DAANet based on residual edge feature(REF),pyramid dynamic attention(PDA)and dynamic global feature aggregation(DGFA)modules.Taken physician manual segmentation results as references,the results were compared with those of other networks.Results Compared with other networks,DAANet had better value for automatic segmentation of ALCAPA in CTA,which could show the details of irregular margins of left coronary artery with good continuity and high clarity,and the performance parameters were overall better.Conclusion DAANet had better performance for automatic segmentation of ALCAPA in CTA.

Objective:To establish a serum detection method of surface-enhanced Raman spectroscopy (SERS) combining with machine learning for early screening of colorectal cancer (CRC).Methods:Serum samples were collected from 150 CRC patients diagnosed at Jiangdu People′s Hospital, Affiliated to Yangzhou University, and also from 37 healthy subjects. Gold nanohexapod (AuNHs) arrays were prepared using an oil-water interface self-assembly method. A 5 μl serum sample was applied onto the AuNHs array. Scatheless and rapid detection for serum were performed using a Renishaw inVia Raman spectrometer at room temperature with a laser wavelength of 785 nm, exposure time of 10 s, and power of 5 mW. The raw SERS spectra were preprocessed using Savitzky-Golay smoothing, AsLS baseline correction, and Min-Max normalization with Origin 2019 software. Furthermore, the principal component analysis (PCA)-support vector machine (SVM) model was constructed using Python′s scikit-learn library. Leave-One-Out Cross-Validation (LOOCV) was used to evaluate the model′s accuracy, sensitivity, specificity, and area under the curve (AUC).Results:The AuNHs arrays exhibited uniform morphology. The relative standard deviation (RSD) of the SERS intensity at 1 080 cm -1 was 5.69%, and the RSD of the SERS intensity at 1 340 cm -1 was 6.20%. The limit of detection (LOD) of the AuNHs array was 9.42×10 -12 mol/L. The PCA-SVM model achieved an accuracy of 90.91% (170/187), sensitivity of 96.79% (181/187), specificity of 99.47% (186/187), and an AUC of 0.98. The most significant characteristic peaks distinguishing different CRC stages were at 747, 940, 1 000, 1 447, and 1 612 cm -1. Conclusion:The serum detection method based on SERS combined with machine learning can accurately screen CRC with higher accuracy, sensitivity, and specificity, demonstrating potential clinical application value.

Objective:To investigate the effects of baicalin on ferroptosis of mouse fibroblasts (Fbs) under high glucose treatment and its mechanism, and to provide a basis for the treatment of diabetic wounds.Methods:The study was an experimental study. Mouse Fbs were collected and divided into control group with conventional culture, high glucose group treated with glucose at final molarity of 30.0 mmol/L, and low baicalin group and high baicalin group pretreated with baicalin at final molarties of 5 and 10 μmol/L respectively and then treated as that in high glucose group. After 48 h of culture, the cell survival rate was detected by the cell counting kit-8, the reactive oxygen species level in cells was detected by the fluorescent probe method, the levels of malondialdehyde, glutathione, and ferrous ion in cells were detected by colorimetry, and the protein expression levels of solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4) in cells and nuclear factor-erythroid 2-related factor 2 (Nrf2) in cytoplasm and nucleus were detected by Western blotting. Another batch of mouse Fbs were collected and divided into control group, high glucose group, high baicalin group, and high baicalin+ML385 group. The cells in the first three groups were treated as before, the cells in the last group were pretreated with baicalin and ML385 of Nrf2 inhibitor at final molarties of 10 μmol/L and then treated as that in high glucose group. After 48 h of culture, the protein expression levels of SLC7A11 and GPX4 in cells and the protein expression level of Nrf2 in cytoplasm and nucleus were detected as before. Except that the sample number in detecting SLC7A11 and GPX4 was 4, the sample number in detecting other indexes was 3.Results:After 48 h of culture, the cell survival rates in control group, high glucose group, low baicalin group, and high baicalin group were (100.0±10.7)%, (70.0±5.0)%, (80.9±3.2)%, and (91.4±1.9)%, respectively. Compared with those in control group, the cell survival rate, the glutathione level, and SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level were significantly decreased in high glucose group ( P<0.05), and the levels of reactive oxygen species, malondialdehyde, and ferrous ion in cells, and cytoplasmic Nrf2 protein expression level were significantly increased in high glucose group ( P<0.05). Compared with those in high glucose group, the cell survival rate, glutathione level, SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level in low baicalin group and high baicalin group were significantly increased ( P<0.05), the reactive oxygen species and ferrous ion levels in cells, and cytoplasmic Nrf2 protein expression level in low baicalin group and high baicalin group were significantly decreased ( P<0.05), and the malondialdehyde level in cells in high baicalin group was significantly decreased ( P<0.05). Compared with those in low baicalin group, the cell survival rate, glutathione level, SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level in high baicalin group were significantly increased ( P<0.05), and the reactive oxygen species, malondialdehyde, and ferrous ion levels in cells, and cytoplasmic Nrf2 protein expression level in high baicalin group were significantly decreased ( P<0.05). After 48 h of culture, compared with those in control group, the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly decreased ( P<0.05), and the cytoplasmic Nrf2 protein expression level was significantly increased in high glucose group ( P<0.05); compared with those in high glucose group, the cytoplasmic Nrf2 protein expression level was significantly decreased ( P<0.05), and the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly increased in high baicalin group ( P<0.05); compared with those in high baicalin group, the cytoplasmic Nrf2 protein expression level was significantly increased ( P<0.05), and the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly decreased in high baicalin+ML385 group ( P<0.05). Conclusions:Baicalin can inhibit the occurrence of ferroptosis in cells by activating the Nrf2 signaling pathway and up-regulating the expressions of proteins related to SLC7A11/GPX4 axis in Fbs in high glucose treatment, thus increasing the cell survival rate.

Objective To investigate the current situation of off-label use of immune checkpoint inhibitors(ICIs)in China and the cognition of medical staff.Methods From August 31 to September 9,2022,a nationwide survey questionnaire was sent to medical staff in the form of electronic questionnaire.The questionnaire included 13 questions,covering four dimensions:Drug allocation,current situation of medication beyond the instructions,cognition of medication beyond the instructions and current situation of medication beyond the instructions.Results A total of 745 questionnaires were collected.75.70％of respondents reported off-label use of ICIs in their hospitals,with the most common type being off-label indications.The primary reasons for such practices included support from authoritative domestic and international guidelines,clinical research data validation,and approved indications in foreign regulatory documents.85.37％of respondents believed off-label use could offer new hope for patients,while 68.86％considered it unlikely to increase adverse reactions.44.97％of respondents' hospitals had not established off-label use registration systems for ICIs.88.86％of respondents emphasized the need for stricter regulations governing off-label use of immunotherapeutic agents.Conclusion Off-label use of ICIs is common,and there is a lack of unified guidance in clinical practice.It is urgent to form norms and consensus on the management of off-label use of ICIs.

Objective To observe the value of dynamic attention aggregation network(DAANet)for automatic segmentation of anomalous origin of the left coronary artery from the pulmonary artery(ALCAPA)in CT angiography(CTA).Methods CTA data in 30 patients with ALCAPA syndrome were retrospectively enrolled.ALCAPA were segmented in CTA with DAANet based on residual edge feature(REF),pyramid dynamic attention(PDA)and dynamic global feature aggregation(DGFA)modules.Taken physician manual segmentation results as references,the results were compared with those of other networks.Results Compared with other networks,DAANet had better value for automatic segmentation of ALCAPA in CTA,which could show the details of irregular margins of left coronary artery with good continuity and high clarity,and the performance parameters were overall better.Conclusion DAANet had better performance for automatic segmentation of ALCAPA in CTA.

Objective To construct a hybrid decision-making model that integrates knowledge-driven and data-driven approaches,and to apply it to the etiological diagnosis of ventricular tachycardia(VT).Methods Clinical practice guidelines,expert consensus documents,and medical literature in the field of ar-rhythmia diseases from 2018 to 2023 were retrieved as knowledge sources.Retrospective electronic medical re-cord data of VT patients from Fuwai Hospital,Chinese Academy of Medical Sciences & Peking Union Medical College,from 2013 to 2023 were collected as the dataset.A knowledge-driven model was constructed using a knowledge-rule-based approach to establish clinical pathways.A three-class machine learning model for VT eti-ology diagnosis was developed based on real-world data,and the best-performing model was selected as the rep-resentative of the data-driven approach.The machine learning model was embedded into the decision nodes of the clinical pathway in the form of custom operators,forming the hybrid model.The precision,recall,and F1 score of the three models were evaluated.Results Three clinical practice guidelines were included as knowl-edge sources for the knowledge-driven model.A total of 1305 patient records were collected as the dataset,and five machine learning models were constructed,with the XGBoost model performing the best.The hybrid model adopted a knowledge-driven decision-making framework,embedding the XGBoost model into the decision nodes of a two-level classification.The precision,recall,and F1 scores of the three models were as follows:the knowledge-driven model achieved 80.4％,79.1％,and 79.7％;the data-driven model achieved 88.4％,88.5％,and 88.4％;and the hybrid model achieved 90.4％,90.2％,and 90.3％.Conclusions The hybrid model integrating knowledge-driven and data-driven approaches demonstrated higher accuracy,and all its deci-sion outcomes were based on evidence-based practices,aligning more closely with the actual diagnostic reason-ing of clinicians.Further rigorous validation is needed to assess the feasibility of widely applying the hybrid model in the medical field.