Objective:To explore the influencing factors for pneumonia occurrence within three months in patients undergoing partial laryngectomy combined with radiotherapy, and to construct a nomogram prediction model for the risk of pneumonia occurrence.Methods:A total of 165 patients with laryngeal squamous cell carcinoma who underwent partial laryngectomy combined with postoperative radiotherapy in the Affiliated Cancer Hospital of Zhengzhou University from 2017 to 2023 were divided into three groups: a group without pneumonia, a low risk pneumonia group, and a medium to high risk pneumonia group according to the occurrence of pneumonia. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff values of the mean dose to the larynx (Larynx-Dmean) and the mean dose to the pharyngeal constrictor muscles (PCM-Dmean) for predicting the occurrence of pneumonia. Logistic regression analysis was used to screen out the influencing factors of pneumonia within three months after partial laryngectomy combined with radiotherapy, and a nomogram prediction model was constructed.Results:Among the 165 patients, 59 were in the group without pneumonia, 60 were in the group with a low risk of pneumonia, and 46 were in the group with a medium to high risk of pneumonia. The overall incidence of pneumonia was 64.2% (106/165). ROC curve analysis showed that the area under the curve (AUC) of the Larynx-Dmean for predicting the occurrence of pneumonia was 0.876, and the optimal cutoff value was 60.8 Gy. When the Larynx-Dmean was >60.8 Gy, the incidence of pneumonia was 96.7%. The AUC of the PCM-Dmean for predicting the occurrence of pneumonia was 0.747, and the optimal cutoff value was 54.6 Gy. When the PCM-Dmean was >54.6 Gy, the incidence of pneumonia was 74.7%. The AUC of the Larynx-Dmean for predicting the occurrence of medium to high risk pneumonia was 0.987, and the optimal cutoff value was 68.2 Gy. When the Larynx-Dmean was >68.2 Gy, the incidence of medium to high risk pneumonia was 100.0%. The AUC of the PCM-Dmean for predicting the occurrence of medium to high risk pneumonia was 0.850, and the optimal cutoff value was 58.7 Gy. When the PCM-Dmean was >58.7 Gy, the incidence of medium to high risk pneumonia was 85.2%. Multivariate logistic regression analysis showed that the incidence of pneumonia was higher in patients with a history of smoking ( OR=1.54, 95% CI: 1.02-1.74), a higher smoking index ( OR=2.43, 95% CI: 1.16-7.59), a higher Larynx-Dmean ( OR=3.79, 95% CI: 1.25-6.49), and a higher PCM-Dmean ( OR=2.44, 95% CI: 1.53-3.16). A nomogram prediction model for the risk of pneumonia and medium to high risk pneumonia within three months after partial laryngectomy combined with radiotherapy was successfully constructed, with C indices of 0.78 and 0.98, respectively, which had good predictive performance and clinical efficacy. Conclusions:When the Larynx-Dmean was >60.8 Gy and the PCM-Dmean was >54.6 Gy for postoperative radiotherapy after partial laryngectomy, the possibility of pneumonia occurrence in patients within three months increased significantly. Smoking history, smoking index, Larynx-Dmean, and PCM-Dmean were independent influencing factors for the occurrence of pneumonia. The nomogram prediction model constructed based on this can guide clinicians to take intervention measures to prevent the occurrence of pneumonia in patients with laryngeal cancer.

Purpose This study aimed to investigate the expression,function,and molecular mechanisms of ZNF384 in esophageal squamous cell carcinoma(ESCC),as well as its role in tumor progression and chemoresistance.Methods The expression of ZNF384 in ESCC cell lines and tissues was assessed using RT-qPCR.Correlations with TNM stage,invasion depth,lymph node metastasis,and prognosis were evaluated.In vitro assays were performed to examine the effects of ZNF384 on ESCC cell proliferation,migration,invasion,and chemosensitivity.Dual-luciferase reporter assays were conducted to determine the interaction between ZNF384 and FZD3,and to assess the activation of the Wnt signaling pathway.Results ZNF384 expression was significantly upregulated in ESCC cell lines and tissues(P＜0.01).Elevated ZNF384 expression was associated with advanced TNM stage,greater invasion depth,lymph node metastasis,and poor prognosis(P＜0.05).Functional assays demonstrated that ZNF384 overexpression promo-ted ESCC cell proliferation,migration,and invasion(all P＜0.01),whereas ZNF384 knockdown inhibited these processes and enhanced chemosensitivity to cisplatin(all P＜0.01).Mechanistic studies showed that ZNF384 directly bound to the FZD3 promoter,upregulated FZD3 expression,and activated the Wnt signaling pathway(P＜0.05).Overexpression of FZD3 partially reversed the inhibitory effects of ZNF384 knockdown on cell malignancy and chemore-sistance(P＜0.05).Conclusion ZNF384 promotes ESCC progression and reduces chemosensitivity through activa-tion of the FZD3/Wnt signaling pathway,suggesting its potential as a therapeutic target in ESCC.

Objective To develop a data-driven model for estimating tangential ground reaction force(GRFt)from lower limb kinematic data and select the most suitable input based on a balance between input quantity and estimation accuracy,with the aim of measuring GRFt in outdoor gait experiments.Methods Gait data from ten subjects walking at five different inclines(-10°,-5°,0°,5°,10°)were used to train two data-driven models,namely a backpropagation neural network(BPNN)-based model and a polynomial sparse identification(PSI)-based model.The performance of these models was evaluated using eight kinematic data combinations and the normal ground reaction force(GRFn)as inputs to determine the optimal model and input combination.Results Under the same input dimensionality,the combination of hip-knee joint angles proved more accurate in estimating GRF,than the knee-ankle joint angle combination.Specifically,the BPNN and PSI models based on the former combination predicted GRF,with errors of 1.61％BW(body weight)and 1.84％BW,respectively,while the latter combination resulted in errors of 2.82％BW and 3.15％BW.When GRFn and all joint angles were used as inputs,the model's prediction error was only 1.46％BW.Conclusions The combination of GRFn and hip-knee joint angles achieves an optimal balance between computational complexity and estimation accuracy.This study supports the accurate estimation of GRF,in outdoor gait testing.

Objective To develop a data-driven model for estimating tangential ground reaction force(GRFt)from lower limb kinematic data and select the most suitable input based on a balance between input quantity and estimation accuracy,with the aim of measuring GRFt in outdoor gait experiments.Methods Gait data from ten subjects walking at five different inclines(-10°,-5°,0°,5°,10°)were used to train two data-driven models,namely a backpropagation neural network(BPNN)-based model and a polynomial sparse identification(PSI)-based model.The performance of these models was evaluated using eight kinematic data combinations and the normal ground reaction force(GRFn)as inputs to determine the optimal model and input combination.Results Under the same input dimensionality,the combination of hip-knee joint angles proved more accurate in estimating GRF,than the knee-ankle joint angle combination.Specifically,the BPNN and PSI models based on the former combination predicted GRF,with errors of 1.61％BW(body weight)and 1.84％BW,respectively,while the latter combination resulted in errors of 2.82％BW and 3.15％BW.When GRFn and all joint angles were used as inputs,the model's prediction error was only 1.46％BW.Conclusions The combination of GRFn and hip-knee joint angles achieves an optimal balance between computational complexity and estimation accuracy.This study supports the accurate estimation of GRF,in outdoor gait testing.

Purpose This study aimed to investigate the expression,function,and molecular mechanisms of ZNF384 in esophageal squamous cell carcinoma(ESCC),as well as its role in tumor progression and chemoresistance.Methods The expression of ZNF384 in ESCC cell lines and tissues was assessed using RT-qPCR.Correlations with TNM stage,invasion depth,lymph node metastasis,and prognosis were evaluated.In vitro assays were performed to examine the effects of ZNF384 on ESCC cell proliferation,migration,invasion,and chemosensitivity.Dual-luciferase reporter assays were conducted to determine the interaction between ZNF384 and FZD3,and to assess the activation of the Wnt signaling pathway.Results ZNF384 expression was significantly upregulated in ESCC cell lines and tissues(P＜0.01).Elevated ZNF384 expression was associated with advanced TNM stage,greater invasion depth,lymph node metastasis,and poor prognosis(P＜0.05).Functional assays demonstrated that ZNF384 overexpression promo-ted ESCC cell proliferation,migration,and invasion(all P＜0.01),whereas ZNF384 knockdown inhibited these processes and enhanced chemosensitivity to cisplatin(all P＜0.01).Mechanistic studies showed that ZNF384 directly bound to the FZD3 promoter,upregulated FZD3 expression,and activated the Wnt signaling pathway(P＜0.05).Overexpression of FZD3 partially reversed the inhibitory effects of ZNF384 knockdown on cell malignancy and chemore-sistance(P＜0.05).Conclusion ZNF384 promotes ESCC progression and reduces chemosensitivity through activa-tion of the FZD3/Wnt signaling pathway,suggesting its potential as a therapeutic target in ESCC.

Objective:To explore the influencing factors for pneumonia occurrence within three months in patients undergoing partial laryngectomy combined with radiotherapy, and to construct a nomogram prediction model for the risk of pneumonia occurrence.Methods:A total of 165 patients with laryngeal squamous cell carcinoma who underwent partial laryngectomy combined with postoperative radiotherapy in the Affiliated Cancer Hospital of Zhengzhou University from 2017 to 2023 were divided into three groups: a group without pneumonia, a low risk pneumonia group, and a medium to high risk pneumonia group according to the occurrence of pneumonia. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff values of the mean dose to the larynx (Larynx-Dmean) and the mean dose to the pharyngeal constrictor muscles (PCM-Dmean) for predicting the occurrence of pneumonia. Logistic regression analysis was used to screen out the influencing factors of pneumonia within three months after partial laryngectomy combined with radiotherapy, and a nomogram prediction model was constructed.Results:Among the 165 patients, 59 were in the group without pneumonia, 60 were in the group with a low risk of pneumonia, and 46 were in the group with a medium to high risk of pneumonia. The overall incidence of pneumonia was 64.2% (106/165). ROC curve analysis showed that the area under the curve (AUC) of the Larynx-Dmean for predicting the occurrence of pneumonia was 0.876, and the optimal cutoff value was 60.8 Gy. When the Larynx-Dmean was >60.8 Gy, the incidence of pneumonia was 96.7%. The AUC of the PCM-Dmean for predicting the occurrence of pneumonia was 0.747, and the optimal cutoff value was 54.6 Gy. When the PCM-Dmean was >54.6 Gy, the incidence of pneumonia was 74.7%. The AUC of the Larynx-Dmean for predicting the occurrence of medium to high risk pneumonia was 0.987, and the optimal cutoff value was 68.2 Gy. When the Larynx-Dmean was >68.2 Gy, the incidence of medium to high risk pneumonia was 100.0%. The AUC of the PCM-Dmean for predicting the occurrence of medium to high risk pneumonia was 0.850, and the optimal cutoff value was 58.7 Gy. When the PCM-Dmean was >58.7 Gy, the incidence of medium to high risk pneumonia was 85.2%. Multivariate logistic regression analysis showed that the incidence of pneumonia was higher in patients with a history of smoking ( OR=1.54, 95% CI: 1.02-1.74), a higher smoking index ( OR=2.43, 95% CI: 1.16-7.59), a higher Larynx-Dmean ( OR=3.79, 95% CI: 1.25-6.49), and a higher PCM-Dmean ( OR=2.44, 95% CI: 1.53-3.16). A nomogram prediction model for the risk of pneumonia and medium to high risk pneumonia within three months after partial laryngectomy combined with radiotherapy was successfully constructed, with C indices of 0.78 and 0.98, respectively, which had good predictive performance and clinical efficacy. Conclusions:When the Larynx-Dmean was >60.8 Gy and the PCM-Dmean was >54.6 Gy for postoperative radiotherapy after partial laryngectomy, the possibility of pneumonia occurrence in patients within three months increased significantly. Smoking history, smoking index, Larynx-Dmean, and PCM-Dmean were independent influencing factors for the occurrence of pneumonia. The nomogram prediction model constructed based on this can guide clinicians to take intervention measures to prevent the occurrence of pneumonia in patients with laryngeal cancer.

Objective:To develop the Nutrition Impact Symptom Scale for Colorectal Cancer Patients.Methods:Guided by the theory of unpleasant symptoms, the initial draft of the scale was formed through literature research, expert consultation, and small sample pre-survey. From March to May 2023, convenience sampling was used to select 127 colorectal cancer patients who visited Jiangsu Cancer Hospital as the research subject for item analysis and reliability and validity testing of the scale.Results:The final scale consisted of five dimensions and a total of 17 items. The content validity index of the scale was from 0.83 to 1.00, with an average content validity index of 0.97. Exploratory factor analysis extracted five common factors, and the cumulative variance contribution rate was 61.622%. The total Cronbach's α coefficient of the scale was 0.708, and the coefficients for each dimension were 0.762, 0.642, 0.625, 0.510, and 0.644, respectively. The half reliability coefficient of the scale was 0.824.Conclusions:The development process of the Nutrition Impact Symptom Scale for Colorectal Cancer Patients is scientific, with good reliability and validity, and can be used to evaluate the nutrition impact symptom of colorectal cancer patients.

Objective To observe the value of multimodal models established combined 18F-FDG PET/CT radiomics with clinical data for evaluating response of locally advanced head and neck squamous cell carcinoma(LA-HNSCC)to neoadjuvant immuno-chemotherapy.Methods Totally 213 LA-HNSCC patients were retrospectively enrolled and randomized into training set(n=170)and test set(n=43)at the ratio of 8∶2.Radiomics features of tumors on 18F-FDG PET/CT were extracted and selected from training set,and the independent clinical predictors were screened with sequential univariate and multivariate logistic regressions.Radiomics models,clinical models and combined multimodal models were constructed using different algorithms,including adaptive boosting(AdaBoost),decision tree,naive Bayes,random forest(RF),support vector machine(SVM)and extreme gradient boosting(XGBoost),respectively.The receiver operating characteristic(ROC)curves were drawn,and the area under the curves(AUC)were calculated to assess the efficacy of each model for predicting the response of LA-HNSCC to neoadjuvant immuno-chemotherapy,and the decision curve analysis(DCA)was performed to explore the net benefit of each model.Results Totally 110 radiomics features were selected,and CD4/CD8 ratio was the independent clinical predictor of the response of LA-HNSCC to neoadjuvant immuno-chemotherapy.Models based on AdaBoost and XGBoost algorithms had high and stable efficacy for predicting tumor response to neoadjuvant immuno-chemotherapy,among which the multimodal models had better performance(AUC=0.943,0.930)than radiomics models(AUC=0.939,0.925)and clinical models(AUC=0.903,0.910)in test set(all P＜0.05).Conclusion Multimodal models established combined 18F-FDG PET/CT radiomics with CD4/CD8 ratio were more effective for predicting response of LA-HNSCC to neoadjuvant immuno-chemotherapy than any single model.

Objective:To investigate the dosimetric factors associated with acute nausea and vomiting (RINV) during intensity modulated radiotherapy for nasopharyngeal carcinoma.Methods:General clinical data and organs at risk (OAR) doses from 130 newly diagnosed early nasopharyngeal carcinoma patients who received radiation therapy alone in Henan Cancer Hospital from February 2018 to February 2023 were retrospectively analyzed. Dosimetric parameters were recorded, and the correlation between the parameters and the degree of nausea and vomiting was statistically analyzed using univariate and multivariate logistic regression models.Results:All 130 patients had symptoms of ≥ grade 1 nausea and vomiting. In the comparison of dosimetric parameters between patients with < grade 2 and ≥ grade 2 nausea, except the brainstem V 20 Gy, all parameters showed statistically significant differences (all P<0.05). The inner ear D max, and D max, D mean, V 10 Gy, V 20 Gy, V 30 Gy of the throat, oral cavity, pharyngeal constrictor, dorsal vagal complex (DVC) showed statistically significant differences between patients with grade 1 and grade 2 nausea (all P<0.05). The results of multivariate regression analysis showed that DVC V 30 Gy was a significant influencing factor in predicting the severity of nausea ( OR=73.95, 95% CI: 4.66-1172.60, P<0.001), and there was a significant correlation between oral V 30 Gy and the severity of vomiting ( OR=37.69, 95% CI: 1.26-1125.42, P=0.04). Conclusions:Even if OAR are exposed to lower doses of radiation, nausea or vomiting symptoms can still occur. The occurrence of RINV is significantly associated with DVC and oral radiation doses.

Spermatogenesis is a continual process that occurs in the testes, in which diploid spermatogonial stem cells (SSCs) differentiate and generate haploid spermatozoa. This highly efficient and intricate process is orchestrated at multiple levels. N⁶-methyladenosine (m⁶A), an epigenetic modification prevalent in mRNAs, is implicated in the transcriptional regulation during spermatogenesis. However, the dynamics of m⁶A modification in non-rodent mammalian species remains unclear. Here, we systematically investigated the profile and role of m⁶A during spermatogenesis in pigs. By analyzing the transcriptomic distribution of m⁶A in spermatogonia, spermatocytes, and round spermatids, we identified a globally conserved m⁶A pattern between porcine and murine genes with spermatogenic function. We found that m⁶A was enriched in a group of genes that specifically encode the metabolic enzymes and regulators. In addition, transcriptomes in porcine male germ cells could be subjected to the m⁶A modification. Our data show that m⁶A plays the regulatory roles during spermatogenesis in pigs, which is similar to that in mice. Illustrations of this point are three genes (SETDB1, FOXO1, and FOXO3) that are crucial to the determination of the fate of SSCs. To the best of our knowledge, this study for the first time uncovers the expression profile and role of m⁶A during spermatogenesis in large animals and provides insights into the intricate transcriptional regulation underlying the lifelong male fertility in non-rodent mammalian species.
Animals ; Male ; Mice ; Cell Differentiation/genetics* ; Mammals/metabolism* ; Methylation ; RNA, Messenger/metabolism* ; Spermatogenesis/genetics* ; Spermatozoa/metabolism* ; Swine/genetics* ; Testis/metabolism* ; Transcriptome ; RNA Methylation/genetics*