ObjectiveTo develop a community-family management model for older adults with mild cognitive impairment (MCI) and to formulate detailed application specifications, and to fully leverage the initiative of communities and families under limited resource conditions, for achieving community-based early detection and early intervention for older adults with MCI. MethodsA systematic literature review was conducted to identify pertinent publications. Corpus-based research methodologies were employed to extract, refine, integrate and synthesize management elements, thereby establishing the specific content and service processes for each stage of the management model. Utilizing the 5W2H analytical framework, essential elements such as management stakeholders, target populations, content and methods for each stage were delineated. The model and its application guidelines were finalized through expert consultation and demonstration. ResultsAn expert evaluation of the management model yielded mean scores of 4.84, 4.32 and 4.84 for acceptability, feasibility and systematicity, respectively. By integrating the identified core elements with expert ratings and feedback, the final iteration of the community-family management model for older adults with MCI was formulated. This model comprised of five stages: screening and identification, comprehensive assessment, intervention planning, monitoring and referral pathways to ensure implementation, and enhanced support for communities, family members and caregivers. Additionally, it included 18 specific application guidelines. ConclusionThe proposed management model may theoretically help delay cognitive decline, improve cognitive function and potentially promote reversal from MCI to normal cognition. It may also enhance the awareness and coping capacity of older adults and their families, strengthen community healthcare professionals' ability to early identify and manage MCI.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To explore the efficacy of letrozole combined with palbociclib in the treatment of hormone receptor +/human epidermal growth factor receptor-2 - (HR +/HER2 -) advanced breast cancer and its influence on serum thymidine kinase 1 (TK1) and proliferating cell nuclear antigen (Ki67) levels. Methods:A total of 82 patients with HR +/HER2 - advanced breast cancer, all admitted from Jan. 2022 to Jan. 2024 from Department of Oncology, Affiliated Hospital of Jining Medical University, were assigned to the control group ( n=41, letrozole) and the study group ( n=41, letrozole + palbociclib) according to the random number table. The therapeutic effect, tumor markers, immune function and serum TK1 and Ki67 levels were compared between the two groups. Results:The study group higher objective response rate and disease control rate than the other group [14.63% (6/41) and 85.37% (35/41) vs. 0.00% (0/41) and 58.54% (24/41) ] (Continuity correction χ2/χ2=4.50, 7.31, P<0.05). After treatment, carbohydrate antigen 153 (CA153), CA125 and carcinoembryonic antigen (CEA) in the study group were lower than the control group [ (12.17±3.19) U/mL, (23.57±3.35) U/mL and (19.51±4.13) ng/mL vs (24.37±5.25) U/mL, (35.16±5.08) U/mL, (34.28±5.72) ng/mL] ( t=12.72, 12.20, 13.41, P<0.05), serum TK1 and Ki67 levels were also lower [ (3.61±0.75) pmol/L and (7.89±1.16) ng/mL vs. (4.76±0.88) pmol/L and (10.85±1.94) ng/mL] ( t=6.37, 8.39, P<0.05). After treatment, CD3 +, CD4 +, CD4 +/CD8 + higher than the control group [ (48.64±5.88) %, (31.34±4.06) %, (1.22±0.27) vs. (43.16±6.09) %, (27.04±3.35) %, (0.87±0.35) ] ( t=4.15, 5.23, 5.07, P<0.05), while CD8 + was lower [ (25.73±4.11) % vs. (30.94±4.47) %] ( t = 5.49, P<0.05) . Conclusions:Letrozole combined with palbociclib is effective in the treatment of HR +/HER2 - advanced breast cancer and can reduce tumor markers and serum TK1 and Ki67 levels in patients.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective·To investigate the role of HEN methyltransferase 1(HENMT1)in the proliferation and migration of gastric cancer(GC)and its potential molecular mechanisms.Methods·The expression of HENMT1 in GC was examined using bioinformatics databases,Western blotting and quantitative real-time PCR(qPCR).Kaplan-Meier Plotter and BEST online tools were used to analyze the correlations between HENMT1 expression and overall survival,perineural invasion,subtypes,tumor location and Lauren classification in clinical GC patients.GC cells were cultured in vitro and treated with small interfering RNA(siRNA)targeting HENMT1 and HENMT1 overexpression vectors,in combination with a PI3K activator(740 Y-P)or PI3K inhibitor(3-MA).The roles of HENMT1 in GC cell proliferation and migration were assessed using cell counting kit-8(CCK-8)assay,colony formation assay,wound healing assay and Transwell migration assay.Results·HENMT1 was significantly upregulated in GC and positively associated with perineural invasion.Its expression was closely related to GC subtypes,being most pronounced in the proliferative subtype,and was higher in intestinal-type GC according to the Lauren classification.However,HENMT1 expression showed no significant correlation with overall survival or tumor location(including gastric body,cardia,antrum and whole stomach).Functional experiments demonstrated that silencing HENMT1 inhibited GC cell proliferation and migration,whereas overexpression of HENMT1 enhanced these capabilities.Mechanistically,silencing HENMT1 reduced the levels of phosphorylated PI3K,AKT and mTOR,as well as their total protein expression.Conversely,HENMT1 overexpression upregulated these proteins.Moreover,siHENMT1 combined with the PI3K activator 740 Y-P effectively reversed the proliferation and migration effects induced by 740 Y-P,while overexpressed HENMT1 combined with the PI3K inhibitor 3-MA reversed the suppressive effects of 3-MA on GC cell proliferation and migration.Conclusion·HENMT1 is highly expressed in GC and positively regulates the proliferation and migration of gastric cancer cells by activating the PI3K-AKT-mTOR signaling pathway.

Objective To investigate the nutritional quality characteristics of vitamin D3-fortified yogurt and explore its improving effect on vitamin D metabolism in the body under simulated weightlessness,thereby providing a theoretical basis for the development of functional foods.Methods Using reconstituted milk as the matrix and Vitamin D3(VD3)microcapsule powder as the fortifier,VD3-fortified yogurt was prepared.A systematic study was conducted to investigate the effects of different gradients(1.25 μg/100 mL,2.50 μg/100 mL,3.75 μg/100 mL,5.00 μg/100 mL,6.25 μg/100 mL)of VD3 microcapsule addition on its quality characteristics(titratable acidity,solid content,water-holding capacity,syneresis).In vivo assessments were conducted using a Sprague-Dawley(SD)rat tail-suspension model to simulate weightlessness.Levels in serum 25(OH)D3,1,25-(OH)2D3,calcium(Ca),and phosphorus(P)were detected using the enzyme-linked immunosorbent assay(ELISA)to evaluate its metabolic capacity.Results During fermentation(3 h),titratable acidity of VD?-fortified yogurt initially increased,then decreased,and eventually stabilized with rising microcapsule dosage,while total solid content remained consistent.WHC exhibited an initial increase followed by a decline,whereas syneresis showed an inverse trend.At an optimal dosage of 3.75 μg/100 mL,the yogurt displayed a dense and uniform network structure,characterized by non-Newtonian fluid behavior with shear-thinning properties.This formulation demonstrated robust structural stability under high-frequency mechanical stress,alongside desirable textural,flavor,and sensory attributes.Animal experiments revealed that the serum concentrations of 25(OH)D3,1,25-(OH)2D3,calcium,and phosphorus in the vitamin D?-fortified yogurt intervention group were significantly higher than those in the tail-suspended control group(P<0.05).Conclusion VD? microencapsulation technology effectively preserves and enhances the nutritional quality characteristics of yogurt and mitigates vitamin D metabolic dysregulation under simulated weightlessness.

Objective·To investigate the role of HEN methyltransferase 1(HENMT1)in the proliferation and migration of gastric cancer(GC)and its potential molecular mechanisms.Methods·The expression of HENMT1 in GC was examined using bioinformatics databases,Western blotting and quantitative real-time PCR(qPCR).Kaplan-Meier Plotter and BEST online tools were used to analyze the correlations between HENMT1 expression and overall survival,perineural invasion,subtypes,tumor location and Lauren classification in clinical GC patients.GC cells were cultured in vitro and treated with small interfering RNA(siRNA)targeting HENMT1 and HENMT1 overexpression vectors,in combination with a PI3K activator(740 Y-P)or PI3K inhibitor(3-MA).The roles of HENMT1 in GC cell proliferation and migration were assessed using cell counting kit-8(CCK-8)assay,colony formation assay,wound healing assay and Transwell migration assay.Results·HENMT1 was significantly upregulated in GC and positively associated with perineural invasion.Its expression was closely related to GC subtypes,being most pronounced in the proliferative subtype,and was higher in intestinal-type GC according to the Lauren classification.However,HENMT1 expression showed no significant correlation with overall survival or tumor location(including gastric body,cardia,antrum and whole stomach).Functional experiments demonstrated that silencing HENMT1 inhibited GC cell proliferation and migration,whereas overexpression of HENMT1 enhanced these capabilities.Mechanistically,silencing HENMT1 reduced the levels of phosphorylated PI3K,AKT and mTOR,as well as their total protein expression.Conversely,HENMT1 overexpression upregulated these proteins.Moreover,siHENMT1 combined with the PI3K activator 740 Y-P effectively reversed the proliferation and migration effects induced by 740 Y-P,while overexpressed HENMT1 combined with the PI3K inhibitor 3-MA reversed the suppressive effects of 3-MA on GC cell proliferation and migration.Conclusion·HENMT1 is highly expressed in GC and positively regulates the proliferation and migration of gastric cancer cells by activating the PI3K-AKT-mTOR signaling pathway.

Objective:To explore the efficacy of letrozole combined with palbociclib in the treatment of hormone receptor +/human epidermal growth factor receptor-2 - (HR +/HER2 -) advanced breast cancer and its influence on serum thymidine kinase 1 (TK1) and proliferating cell nuclear antigen (Ki67) levels. Methods:A total of 82 patients with HR +/HER2 - advanced breast cancer, all admitted from Jan. 2022 to Jan. 2024 from Department of Oncology, Affiliated Hospital of Jining Medical University, were assigned to the control group ( n=41, letrozole) and the study group ( n=41, letrozole + palbociclib) according to the random number table. The therapeutic effect, tumor markers, immune function and serum TK1 and Ki67 levels were compared between the two groups. Results:The study group higher objective response rate and disease control rate than the other group [14.63% (6/41) and 85.37% (35/41) vs. 0.00% (0/41) and 58.54% (24/41) ] (Continuity correction χ2/χ2=4.50, 7.31, P<0.05). After treatment, carbohydrate antigen 153 (CA153), CA125 and carcinoembryonic antigen (CEA) in the study group were lower than the control group [ (12.17±3.19) U/mL, (23.57±3.35) U/mL and (19.51±4.13) ng/mL vs (24.37±5.25) U/mL, (35.16±5.08) U/mL, (34.28±5.72) ng/mL] ( t=12.72, 12.20, 13.41, P<0.05), serum TK1 and Ki67 levels were also lower [ (3.61±0.75) pmol/L and (7.89±1.16) ng/mL vs. (4.76±0.88) pmol/L and (10.85±1.94) ng/mL] ( t=6.37, 8.39, P<0.05). After treatment, CD3 +, CD4 +, CD4 +/CD8 + higher than the control group [ (48.64±5.88) %, (31.34±4.06) %, (1.22±0.27) vs. (43.16±6.09) %, (27.04±3.35) %, (0.87±0.35) ] ( t=4.15, 5.23, 5.07, P<0.05), while CD8 + was lower [ (25.73±4.11) % vs. (30.94±4.47) %] ( t = 5.49, P<0.05) . Conclusions:Letrozole combined with palbociclib is effective in the treatment of HR +/HER2 - advanced breast cancer and can reduce tumor markers and serum TK1 and Ki67 levels in patients.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.