Objective To explore latent classes of behavioural and psychological symptoms in the patients with Alzheimer's disease(AD)and to identify the factors influencing the latent classes and provide a basis for fomulating personalized nursing measures.Methods Convenience sampling was employed to recruit 361 AD inpatients from our hospital between November 2023 and May 2024 for this cross-sectional study.A general data questionnaire,the neuropsychiatric inventory questionnaire,Monteria cognitive assessment scale,activity of daily life scale,and mini-nutritional assessment scale were used in the survey.Latent class analysis was conducted to analyse the data acquired from the survey.Univariate analysis and multiple Logistic regression analysis were used to identify the factors influencing latent classes.Results Toally 346 patients finished the study.It was found that a 72.5%of AD patients developed behavioural and psychological symptoms.The symptoms were categorised into three classes:low symptom-apathy,middle symptom-emotional disturbance and high symptom-behaviour disorder.The course of disease,cognitive function,daily living ability and nutritional status were identified as the factors that influenced the latent classes(all P<0.05).Conclusion AD patients with low cognitive function,poor daily living ability,malnutrition and a course of disease over 5 years are at high risks of behavioural and psychological symptoms which are heterogeneous.Care providers are advised to propose personalised care strategies to improve the behavioural and psychological symptoms.

Objective:To investigate the clinical characteristics and treatment of human immunodeficiency virus (HIV) negative adult disseminated Talaromyces marneffei (TSM) infection, so as to improve the diagnosis and treatment of this disease.Methods:While two HIV-negative adult patients with disseminated T. Marneffei infection were reported, papers published between 1970 and February 2024 were collected from CNKI, Wanfang and Chongqing Weipu databases, and patient data meeting diagnostic criteria were collected. A total of 34 HIV-negative adults with disseminated T. Marneffei infection were collected. The data of 34 patients with this disease were retrospectively analyzed, and the demographic distribution, systematic signs, examination results, complications, diagnosis and treatment plan and effect of this disease were summarized.Results:Among the 34 patients, the ratio of male to female patients was 21∶13. The median age of onset was 51 years, ranging from 24 to 70 years. The incidence area was more common in the south of China. The most common clinical manifestation was fever. 70.6%(24/34) of patients were misdiagnosed, most often with tuberculosis. The methods of diagnosis were as follows: 26 cases were diagnosed by fungal culture, 5 cases by high-throughput sequencing and 3 cases by direct microscopy. 32 patients received antifungal therapy, 9 were cured, 10 improved, 2 died, 4 relapsed, 4 patients were effective (but the outcome was unknown), 2 patients had poor effect, and 1 patient had unknown effect. Two patients died soon after admission due to rapid disease progression.Conclusions:The symptoms of HIV negative adults infected with T. Marneffei are varied and may involve multiple systems. Infection is often misdiagnosed. Early identification and fungal culture can improve the detection rate. High-throughput sequencing is a relatively mature diagnostic technology.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.

Objective To analyze the ecological suitability of Codonopsis pilosula;To provide theoretical reference for expanding the planting scale of Codonopsis pilosula in Shanxi Province.Methods Information on the distribution of Codonopsis pilosula samples through the fourth survey of TCM resources in Shanxi Province and literature review;the MaxEnt model and ArcGIS 10.8 geographic information system software were used to analyze the ecological factors affecting the distribution of Codonopsis Radix in Shanxi Province,and the suitable distribution areas of Codonopsis pilosula in Shanxi Province were predicted.Results The predicted distribution areas of Codonopsis pilosula in Shanxi Province by the model were highly consistent with the actual distribution area;the AUC of the training set was 0.945,indicating good prediction results.The predominant ecological factors(contributing)impacting the distribution of Codonopsis pilosula included vegetation type(31.1%),the standard deviation of seasonal temperature fluctuations(25.0%),slope(8.3%),mean January precipitation(5.3%),mean May precipitation(5.0%),and elevation(4.9%)etc.The optimal vegetation types conducive to the proliferation of Codonopsis pilosula were identified as temperate deciduous shrubs,temperate grasslands,temperate coniferous forests,and temperate deciduous broad-leaved forests.The standard deviation of seasonal temperature change was within the range of 92 to 108,the slope gradient was from 14° to 30°,mean January precipitation was of 4 to 6.8 mm,mean May precipitation was of 33.5 to 58 mm,and elevation ranged from 1 100 to 2 800 meters.Codonopsis pilosula was mainly distributed in Lucheng,Qinxian and Qinyuan counties in the eastern part of Taiyue Mountain in Changzhi City;Pu County,Fenxi County,Fenyang City of Lyuliang City in the Lyuliang Mountain Range and Yushe County of Jinzhong City in the northern part of Taiyue Mountain.The most suitable area in Shanxi Province was 14 109.67 km2,the suitable area encompassed 22 837.62 km2,the relatively suitable area covered 41 982.96 km2,while the unsuitable area extended over 77 769.75 km2.Conclusion The geographical distribution data of Codonopsis pilosula resources in Shanxi Province may serve as a basis for further examination of regional zoning,with the establishment of wild cultivation bases for Codonopsis pilosula in proximity to various mountain ranges,such as the Taihang Mountains.Moreover,the artificial cultivation conditions can be modified in accordance with the optimal growth environment of Codonopsis pilosula,thereby optimizing the management of Codonopsis resources.

Objective:To investigate the clinical characteristics and treatment of human immunodeficiency virus (HIV) negative adult disseminated Talaromyces marneffei (TSM) infection, so as to improve the diagnosis and treatment of this disease.Methods:While two HIV-negative adult patients with disseminated T. Marneffei infection were reported, papers published between 1970 and February 2024 were collected from CNKI, Wanfang and Chongqing Weipu databases, and patient data meeting diagnostic criteria were collected. A total of 34 HIV-negative adults with disseminated T. Marneffei infection were collected. The data of 34 patients with this disease were retrospectively analyzed, and the demographic distribution, systematic signs, examination results, complications, diagnosis and treatment plan and effect of this disease were summarized.Results:Among the 34 patients, the ratio of male to female patients was 21∶13. The median age of onset was 51 years, ranging from 24 to 70 years. The incidence area was more common in the south of China. The most common clinical manifestation was fever. 70.6%(24/34) of patients were misdiagnosed, most often with tuberculosis. The methods of diagnosis were as follows: 26 cases were diagnosed by fungal culture, 5 cases by high-throughput sequencing and 3 cases by direct microscopy. 32 patients received antifungal therapy, 9 were cured, 10 improved, 2 died, 4 relapsed, 4 patients were effective (but the outcome was unknown), 2 patients had poor effect, and 1 patient had unknown effect. Two patients died soon after admission due to rapid disease progression.Conclusions:The symptoms of HIV negative adults infected with T. Marneffei are varied and may involve multiple systems. Infection is often misdiagnosed. Early identification and fungal culture can improve the detection rate. High-throughput sequencing is a relatively mature diagnostic technology.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.

Objective To explore latent classes of behavioural and psychological symptoms in the patients with Alzheimer's disease(AD)and to identify the factors influencing the latent classes and provide a basis for fomulating personalized nursing measures.Methods Convenience sampling was employed to recruit 361 AD inpatients from our hospital between November 2023 and May 2024 for this cross-sectional study.A general data questionnaire,the neuropsychiatric inventory questionnaire,Monteria cognitive assessment scale,activity of daily life scale,and mini-nutritional assessment scale were used in the survey.Latent class analysis was conducted to analyse the data acquired from the survey.Univariate analysis and multiple Logistic regression analysis were used to identify the factors influencing latent classes.Results Toally 346 patients finished the study.It was found that a 72.5%of AD patients developed behavioural and psychological symptoms.The symptoms were categorised into three classes:low symptom-apathy,middle symptom-emotional disturbance and high symptom-behaviour disorder.The course of disease,cognitive function,daily living ability and nutritional status were identified as the factors that influenced the latent classes(all P<0.05).Conclusion AD patients with low cognitive function,poor daily living ability,malnutrition and a course of disease over 5 years are at high risks of behavioural and psychological symptoms which are heterogeneous.Care providers are advised to propose personalised care strategies to improve the behavioural and psychological symptoms.

Background: Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear. Methods: We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP). Results: We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin. Conclusions PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.

Background: Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear. Methods: We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP). Results: We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin. Conclusions PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.

Background: Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear. Methods: We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP). Results: We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin. Conclusions PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.