Zhunzhun Liu

Objective: To develop and externally validate an interpretable machine learning model for identifying the likelihood of a positive Standardized Swallowing Assessment (SSA) result in people with dementia, particularly in settings where instrumental swallowing assessments are not readily available. Methods: Candidate variables included demographic, physical, oral-health, and mental health variables routinely available in clinical practice. Least absolute shrinkage and selection operator (LASSO) regression was used for variable selection. Four machine learning models were developed and compared: logistic regression, support vector machines, random forest, and AdaBoost. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, calibration, and decision curve analysis. SHAP analysis was applied to enhance model interpretability. A web-based likelihood assessment tool was developed to estimate the individual probability of a concurrent positive SSA result. Results: All four models showed good discrimination. AdaBoost achieved an AUC of 0.918 in internal cross-validation and AUCs of 0.900 and 0.889 in the domain and temporal external validation cohorts, respectively, with sensitivities ranging from 0.879 to 0.901. Since sensitivity was prioritized for case finding, AdaBoost was selected for model interpretation and online-tool development. SHAP analysis ranked body mass index as the leading contributor to the AdaBoost output, followed by number of teeth, eating ability, dietary type, and Clinical Dementia Rating score. Conclusion: The model showed good performance for identifying people likely to have a concurrent positive SSA screening result. The web-based tool may support case finding and referral for further swallowing assessment, but it should not be used as a standalone diagnostic or prognostic instrument. Prospective and geographically diverse validation is required before routine clinical implementation.

Frailty is characterized by an age-related decline in physiological reserve and is closely linked to postoperative outcomes. Early identification of preoperative frailty is therefore essential. This study aims to examine the associations between preoperative frailty and postoperative complications and cognitive impairment in patients with liver cancer, and to identify potential contributing factors. This observational cohort study was conducted at the Affiliated Hospital of Jiangnan University from February to June 2025 and included 115 patients with liver cancer who underwent surgery. Frailty status was assessed using the Fried Phenotype criteria on 1 day before surgery, and cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA) on postoperative day 3. Postoperative complications occurring before discharge were also recorded. A total of 43 patients (37.4%) developed postoperative complications, which may have been associated with preoperative frailty and its components, including exhaustion, grip strength, and low physical activity. Moreover, significantly higher prevalences of postoperative hypoproteinemia and liver function impairment, as well as markedly lower MoCA scores in unadjusted comparisons on postoperative day 3 (continuous outcome) were observed in patients with preoperative frailty. Receiver operating characteristic (ROC) analysis indicated that the frailty score may serve as a predictor of postoperative complications. Preoperative frailty in patients with liver cancer may be associated with postoperative complications, and the frailty score may potentially serve as a predictor of these complications.

Genetically encoded biosensors represent cutting-edge biosensors due to their capabilities in real-time monitoring and precise control in living cells. However, the development of eukaryotic genetically encoded biosensors for new analytes is constrained by the shortage of signal–receptor pairs. Bacterial biosensors have been transferred to eukaryotes to expand the signal detection space, which has achieved remarkable success. However, due to the significant differences between eukaryotic and prokaryotic gene expression systems, optimizing bacterial biosensors has proven challenging. Successful cases indicate that developing orthogonal signal–receptor pairs directly from eukaryotic systems may offer a viable solution. Indeed, the potential of filamentous fungi—a highly diverse group of organisms that share conserved as well as specific signaling and metabolic pathways with yeast and mammalian cells—has been largely overlooked in biosensor development. In this review, we systematically examine biosensing systems in filamentous fungi, summarize their signal recognition receptors, signal transduction pathways, responsive transcription factors, and provide an overview of the biosensors and synthetic tools developed from them. Finally, we highlight the promise and challenges of biosensor development from filamentous fungi and discuss their potential applications.

Genetically encoded biosensors represent a cutting-edge class of biosensors due to real-time monitoring and programmability in living cell. However, the development of eukaryotic genetically encoded biosensors for new analytes is constrained by the shortage of signal–receptor pairs. Bacterial biosensors have been transferred to eukaryote to expand the signal detection space, having achieved remarkable success. However, due to the significant differences between eukaryotic and prokaryotic gene expression systems, optimizing bacterial biosensors has proven challenging. Successful cases indicate that developing orthogonal signal–receptor pairs directly from eukaryotic systems may offer a viable solution. Indeed, the potential of filamentous fungi—a highly diverse group of organisms that share conserved as well as specific signaling and metabolic pathways with yeast or mammalian cells—has been largely overlooked in biosensor development. In this review, we systematically examine sensing systems in filamentous fungi and summarize their signal recognition receptors, signal transduction pathways，responsive transcription factors and describe potential mining strategies for sensing elements from filamentous fungi.

Background: Male nursing students face distinctive challenges in obstetrics and gynecology (OB-GYN) nursing education, influenced by social perceptions and the specialty’s gender dynamics. Objective: This study aimed to develop effective instructional strategies addressing male students’ learning challenges in OB-GYN. Methods: Using a mixed-method design (qualitative interviews, focus groups, expert workshops, Delphi survey), the prototype of instructional strategies was created based on design thinking and the Medical Research Council (MRC) framework. A non-randomized trial (n = 56) tested the 10-week intervention in a 2025 OB-GYN undergraduates’ course at Wuxi Taihu University, assessing academic performance, knowledge application/transfer (teacher-rated), and competency (self-reported). Results: The experimental group demonstrated significantly better knowledge application/transfer skills (t = 2.206, P = 0.034) and higher overall competency levels (t = 2.207– 4.359, P < 0.05) compared to controls. Regression analysis confirmed the instructional strategies (β = 0.298, P < 0.001), academic performance (β = − 1.062, P = 0.001), and knowledge application skills (β = 1.674, P < 0.001) as significant predictors of self-reported competency, explaining 68.5% of variance. Conclusion: The evidence-based instructional strategies effectively enhance practical skills and professional competencies in OB-GYN nursing education. While promising, further multi-center trials with larger samples are recommended to validate these findings and assess long-term impacts on professional development.

The study aimed to establish and validate a nomogram model to predict postoperative delirium (POD) among esophageal cancer resection patients. Clinical data of 396 patients with esophageal cancer who underwent esophagectomy from November 2020 to June 2023 in the electronic medical records of cardiothoracic Surgery, Affiliated Hospital of Jiangnan University. Participants were randomly divided into training and testing sets in a 7:3 ratio. Predictors were screened by Least absolute shrinkage and selection operator (LASSO) regression analysis and a nomogram model was built. The discrimination and consistency of the model were evaluated using the area under the receiver operating characteristic curve (AUC), C-statistic, Brier score, Hosmer-Lemeshow goodness-of-fit test, calibration curve and decision curve analysis (DCA). The results were validated using 1000 bootstraps resampling internal validation and testing set. Among 32 potential predictors, the final prediction model included 6 variables: postoperative pain, postoperative infection, dexmedetomidine use, propofol use, duration of mechanical ventilation, and Prognostic Nutritional Index (PNI). The model showed a good discrimination with an AUC of 0.919 (95% CI: 0.885- 0.953) in the training set, and adjusted to 0.911 (95% CI: 0.878- 0.944) and 0.871 (95% CI: 0.802- 0.940) in the internal validation and the testing set, respectively. ROC curves, calibration curves, DCA curves, C-statistic, Brier score and Hosmer-Lemeshow goodness-of-fit test showed excellent model performance. This study successfully established and validated the first POD prediction model for patients with esophageal cancer resection. It could accurately predict the occurrence of POD and effectively identify the high-risk patients, which is of great significance for improving the risk stratification of the population and for implementing targeted prevention intervention measures.

Background: Obstetrics and Gynecology Nursing (OB-GYN) is a critical yet challenging field of study for male nursing undergraduates due to traditional gender biases and the perception of it being a female-dominated profession. Objective: The study aimed to better understand the experiences of male nursing students in learning OB-GYN. Methods: This study used a qualitative method of phenomenological study approach. The purpose sampling approach was used to recruit participants from April to May 2024. The interviews were recorded and transcribed verbatim. Van Manen’s method of phenomenological hermeneutics was adopted to analyze the text. Results: The study interviewed 10 participants and identified three key themes: (1) negative future appraisal, (2) breaking out of information bubbles, and (3) positive capacity-building among male students. Conclusion: In this study, male nursing undergraduates expressed negative future appraisal, but experienced the growth and gain of personal skills in the learning process. An important finding was that male nursing undergraduates expressed the need to overcome traditional cultural biases. Future OB-GYN class is recommended to introduce male role models for male nursing students, encourage their discussion on gender-bias. Researchers are recommended to investigate the barriers and facilitators in OB-GYN education for male nursing students.

We explored the relationship between benefit finding (BF)/posttraumatic growth (PTG) at baseline and health-related quality of life (HRQOL) at baseline and follow-up in long-term cancer survivors (LTCS; ≥5-year post-diagnosis). HRQOL was assessed in LTCS in 2009-2011 (5- to 16-year post-diagnosis, baseline) and re-assessed in 2018/2019 (14- to 24-year post-diagnosis, follow-up). BF and PTG were measured at baseline; mean scores were dichotomized into 'none-to-low' ( =3). Linear regression models and linear mixed regression models were employed to assess the association of BF/PTG with HRQOL. Of the 6057 baseline participants, 4373 were alive in 2019, of whom 2704 completed the follow-up questionnaire. Cross-sectionally, LTCS with none-to-low BF reported better HRQOL at baseline and at follow-up than LTCS with higher BF. Longitudinally, no difference was found between none-to-low and moderate-to-high BF on the HRQOL change from baseline to follow-up. HRQOL differences between the PTG groups were not statistically significant cross-sectionally and longitudinally, except those participants with moderate-to-high PTG reported higher role functioning and global health status/QOL. Cross-sectionally, BF was significantly negatively related to subscales of HRQOL, while PTG was positively correlated to role functioning and global health status/QOL. The results add further evidence that BF and PTG are two different positive psychological concepts.

Background: Diabetes increases the risk of certain types of cancer. However, the literature regarding the incidence of diabetes after cancer diagnosis is inconsistent. We aimed to assess whether there was a higher incidence of diabetes among cancer patients by performing a systematic review and meta-analysis of results from cohort studies. Methods: A systematic electronic literature search was carried out from cohort studies regarding the incidence of diabetes in cancer patients, using the databases PubMed (MEDLINE), Embase, Web of Science, and the Cochrane Library. Random-effects meta-analyses were conducted to pool the estimates. Results: A total of 34 articles involving 360,971 cancer patients and 1,819,451 cancer-free controls were included in the meta-analysis. An increased pooled relative risk (RR) of 1.42 (95% confidence interval (CI): 1.30–1.54, I² = 95, τ² = 0.0551, p < 0.01) for diabetes in cancer patients was found compared with the cancer-free population. The highest relative risk was observed in the first year after cancer diagnosis (RR = 2.06; 95% CI 1.63–2.60). Conclusions: New-onset diabetes is positively associated with cancer, but this association varies according to cancer type. More prospective studies with large sample sizes and longer follow-up times are advocated to further examine the association and the underlying mechanisms.