With the rapid aging of the global population, the demand for prosthodontic rehabilitation of partial edentulism continues to increase. Among the available treatment options, removable partial dentures remain an essential clinical modality for restoring partially edentulous arches and masticatory function because of their broad indications, minimal invasiveness, and cost-effectiveness. However, unlike fixed prosthodontics, which have undergone substantial digitalization, removable partial denture therapy is characterized by dual tooth-tissue support, complex biomechanics, and highly variable anatomical morphology. As a result, the digital design and fabrication of removable partial dentures have long faced major bottlenecks, including limited standardization, steep learning curves, and heavy dependence on expert experience. In recent years, artificial intelligence (AI) has undergone a paradigm shift from early expert systems to machine learning and deep learning, creating new opportunities to address the complexity and precision demands of removable partial denture design. Based on a comprehensive literature review and our team's clinical experience, this article systematically elaborates on the specific applications and normative standards of AI throughout the entire removable partial denture fabrication workflow. In the data acquisition phase, we emphasize multimodal data fusion and digital pressure impression strategies. In the intelligent diagnosis and planning phase, deep learning is utilized to achieve the automatic identification of edentulous areas and undercuts, while machine learning and expert systems assist in abutment selection and treatment plan generation. Regarding automated design logic, the article analyzes the process from the intelligent planning of the common path of insertion to parametric design based on biomechanical optimization. At the clinical operation level, a standardized human-machine collaborative workflow of “AI generation-clinician review-local fine-tuning” is proposed. In terms of ethics and accountability, the principles of algorithmic transparency and “the clinician as the ultimate responsible subject” are emphasized. Furthermore, integrating clinical practice, this article innovatively proposes a “capability grading system for AI-assisted removable partial denture design (comprising the auxiliary analysis level, the rule-based design level, and the intelligent adaptive level)”. The aim is to offer practical recommendations for dental clinicians, dental technicians, and researchers, thereby facilitating the transition of removable partial denture prosthodontics toward greater precision, intelligence, and standardization.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

Objective:To explore the developmental trajectory and influencing factors of self-management behavior among stroke patients.Methods:A total of 478 ischemic stroke patients admitted to the department of neurology of a grade-Ⅲ hospital in Henan Province from July 2023 to June 2024 were selected as the investigation objects. Baseline data of patients were collected using the general situation questionnaire, stroke knowledge questionnaire, stroke health belief scale, stroke self-management behavior scale and self-rating depression scale. The self-management behavior level of patients was assessed at discharge, 1 month, 3 months and 6 months after discharge. Mplus 7.0 software was used to conduct trajectory analysis of stroke patients' self-management behaviors, and multiple Logistic regression analysis was used to analyze the influencing factors associated with the development trajectory types of different stroke self-management behaviors.Results:The self-management behavior scores of stroke patients at discharge, 1 month, 3 months and 6 months after discharge were 206.59(167.59, 230.57), 169.59(129.73, 196.73), 149.82(120.89, 171.48), and 147.14(123.02, 181.64), respectively. Four trajectory categories were described. Category 1 was low-level pattern of initial decrease followed by stabilization, accounting for 16.95%(81/478)( P<0.001, intercept=2.701). Category 2 was low-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept =2.696). Category 3 was medium-level pattern of initial decrease followed by stabilization, accounting for 57.11%(273/478)( P<0.001, intercept =3.829). Category 4 was high-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept=4.366). The self-management behavior of stroke patients with low level of stroke knowledge, low level of health belief, aged 60 to 70 years old, residence in rural areas and middle school and below education level were more likely to belong to the low level group(all P<0.05). Patients with low depression in the low level group were more likely to be classified as low-level pattern of initial decrease followed by increase( P<0.05). Conclusion:The trajectory category of self-management behavior could be predicted by stroke knowledge level, health belief level, age, place of residence, educational background and depression. Their self-management behavior level may be improved through targeted interventions according to the characteristics of different trajectory categories.

Objective:To understand the feelings and experiences of patients with dizziness caused by cerebrovascular diseases, and to provide a reference basis for the development of nursing intervention measures.Methods:Semi-structured interviews were carried out from November 2024 to February 2025 by phenomenology method. The patients with dizziness caused by cerebrovascular diseases who were hospitalized in the First Affiliated Hospital of Zhengzhou University were selected by purposive sampling method. The interview data were analyzed by the Colaizzi 7-step analysis method to summarize and extract the themes.Results:Finally, 16 patients with dizziness caused by cerebrovascular diseases were interviewed, including 6 males and 10 females, aged 43 to 73 years. The feeling and experience of patients with dizziness caused by cerebrovascular diseases could be summarized into three themes: persistent physical symptoms (physiological function imbalance, the superposition of multiple symptoms); patients had cognitive biases (symptom risk cognitive bias, symptom knowledge cognitive bias, drug effect cognitive bias); patients' self-perceived burden was obvious(physical burden, emotional burden, and economic burden).Conclusions:The patients with dizziness caused by cerebrovascular diseases show multi-dimensional characteristics, and there are many burdens and needs in physiological, psychological and social aspects. We should pay attention to the symptom experience and psychological feelings of such patients, and give targeted health education and multi-dimensional social support.

Objective:To explore the developmental trajectory and influencing factors of self-management behavior among stroke patients.Methods:A total of 478 ischemic stroke patients admitted to the department of neurology of a grade-Ⅲ hospital in Henan Province from July 2023 to June 2024 were selected as the investigation objects. Baseline data of patients were collected using the general situation questionnaire, stroke knowledge questionnaire, stroke health belief scale, stroke self-management behavior scale and self-rating depression scale. The self-management behavior level of patients was assessed at discharge, 1 month, 3 months and 6 months after discharge. Mplus 7.0 software was used to conduct trajectory analysis of stroke patients' self-management behaviors, and multiple Logistic regression analysis was used to analyze the influencing factors associated with the development trajectory types of different stroke self-management behaviors.Results:The self-management behavior scores of stroke patients at discharge, 1 month, 3 months and 6 months after discharge were 206.59(167.59, 230.57), 169.59(129.73, 196.73), 149.82(120.89, 171.48), and 147.14(123.02, 181.64), respectively. Four trajectory categories were described. Category 1 was low-level pattern of initial decrease followed by stabilization, accounting for 16.95%(81/478)( P<0.001, intercept=2.701). Category 2 was low-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept =2.696). Category 3 was medium-level pattern of initial decrease followed by stabilization, accounting for 57.11%(273/478)( P<0.001, intercept =3.829). Category 4 was high-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept=4.366). The self-management behavior of stroke patients with low level of stroke knowledge, low level of health belief, aged 60 to 70 years old, residence in rural areas and middle school and below education level were more likely to belong to the low level group(all P<0.05). Patients with low depression in the low level group were more likely to be classified as low-level pattern of initial decrease followed by increase( P<0.05). Conclusion:The trajectory category of self-management behavior could be predicted by stroke knowledge level, health belief level, age, place of residence, educational background and depression. Their self-management behavior level may be improved through targeted interventions according to the characteristics of different trajectory categories.

Objective To explore the predictive value of quantitative parameters of dual-layer detector spectral CT(DLCT)for Ki-67 expression in solid lung adenocarcinoma.Methods The data of 103 patients were retrospectively collected,and the patients were divided into Ki-67 high expression and Ki-67 low expression groups according to Ki-67 proliferation index.The quantitative parame-ters of DLCT were measured and calculated,and the differences in these parameters between the two groups were compared.The parameters with statistically significant differences were assessed for correlation with Ki-67 expression.The efficacy of DLCT param-eters and combined parameters in predicting Ki-67 expression in solid lung adenocarcinoma were evaluated by receiver operating character-istic(ROC)curve and compared by DeLong test.Results Long diameter,short diameter and smoking history were positively corre-lated with the Ki-67 expression in solid lung adenocarcinoma(r>0,P<0.05).Gender and quantitative parameters of DLCT were nega-tively correlated with the Ki-67 expression in solid lung adenocarcinoma(r<0,P<0.05).The combined parameters of convention and spectral CT had the highest prediction efficiency.Conclusion The quantitative parameters of DLCT can be used to evaluate the Ki-67 expres-sion in solid lung adenocarcinoma.

Objective:To study the genotype and molecular characteristics of Hantavirus causing hemorrhagic fever with renal syndrome (HFRS) in Shenzhen so as to provide basis for the prevention and control.Methods:The serum samples of HFRS patients at acute stage were collected from hospitals, and viral RNA from the sera was extracted as a template for typing detection by real-time fluorescent PCR. The nucleotide sequences of M fragment (G2 segment) and S fragment were amplified by reverse transcription-nested polymerase chain reaction (RT-nested PCR). The PCR products were then sequenced and homology and phylogenetic tree analysis were conducted.Results:In a total of 123 HV IgM antibody positive serum samples were collected in Shenzhen from 2015 to 2023, including 97 males and 26 females. Most of patients were young and middle-aged men. Cases were found throughout the year, with high incidence in spring and early summer. The result of fluorescence PCR showed that among 92 clinical specimens, 63 cases (68.5%) were tested positive for hantavirus genotypes, 59 cases (93.7% of positives) were identified as SEOV and 4 cases (6.3% of positives) as HTNV. Notably, all HTNV-positive patients were male. Analysis on nucleotide homology and phylogenetic tree showed that the difference in nucleotide sequences among SEO viruses in Shenzhen was small, and most of them were S2 subtype except for two cases of S3 subtype. The mutation rate of HTN viruses was high, with two cases of H5 subtype and two cases of H8 subtype.Conclusions:The major genotype of hantavirus causing HFRS in Shenzhen is SEO genotype, especially S2 subtype, which is closely related to some strains in Guangzhou, and has high homology with L99, Z37 and other vaccine strains. The existence of S3 subtype cases was detected for the first time in Shenzhen, while some cases of HTNV were still imported.