Objective To explore the time-varying pattern of potential symptoms in breast cancer patient before and after chemotherapy,and further analyze its influencing factors,aims to provide reference for clinical nursing practice.Methods 233 cases of breast cancer in a tertiary A hospital in Ningxia from June to October,2023 were selected as the research subjects.By the general information questionnaire and the Chinese version of Anderson Symptom Assessment Scale,the potential change of symptoms of breast cancer patients undergoing chemotherapy 1-3 days before the first chemotherapy(T1,233 cases)and 7-14 days after the third or fourth chemotherapy(T2,225 cases)was analyzed.Results 225 cases of breast cancer patients completed 2 surveys,and their symptom characteristics before and after chemotherapy can be divided into 2 categories:a high symptom troubled group and a low symptom troubled group.The high-symptom troubled group has strong stability,and the probability of maintaining the original group is 85.20％,while the low-symptom troubled group is more inclined to change to the high-symptom troubled group,and the transition probability is 26.60％.Logistic regression analysis showed that the mass was located on the left side,and the patients who obtained disease knowledge mainly through the Internet were more likely to change from the high symptom troubled group to the low symptom troubled group,while the patients who were employed,with unsatisfactory sleep at night,and never exercised were more likely to change from the low symptom troubled group to the high symptom troubled group.Conclusion The symptoms of breast cancer patients before and after chemotherapy are heterogeneous.Patients who are on the job,have unsatisfied sleep at night and never exercise are more likely to change from the low-symptom troubled group to the high-symptom troubled group,which suggests that medical staff should identify potential high-risk groups at an early stage,and make full use of the predictive function of symptom characteristics to carry out individualized management based on the dynamic monitoring of symptoms according to different types of population characteristics,so as to reduce the burden of symptoms and improve their quality of life.

Objective:To analyze the applied effect of artificial intelligence(AI)rehabilitation system combined with telemedicine platform in individualized rehabilitation treatment for patients with long-term coma,so as to realize individual management for them.Methods:An AI rehabilitation system that aimed to patients with long-term coma was designed by integrating data of multimodal sensors included inertial sensor,image sensor and bioelectric sensor.A telemedicine platform,which included seven modules(patient management,consultation management,video communication,data transmission,electronic medical records,cost management and system maintenance),was designed by using a browser/server(B/S)architecture.The changes of patients'condition were followed up,and the full process of the management for rehabilitation treatment and the individualization of treatment plan were realized.A total of 60 inpatients whose coma duration exceeded 28 days were selected from the Coma Awakening Center of Dongguan Shipai Hospital between October 1,2021 and September 30,2022.They were randomly divided into control group(n=30)and observation group(n=30)by random number table.The control group received physical therapy and rehabilitation training based on evaluation results of rehabilitation,while the observation group adopted AI rehabilitation system combined with the telemedicine platform to conduct intervention.The consciousness levels,quality of life,hospital stay duration and treatment costs of two group were compared after intervention.Results:The Glasgow Coma Scale(GCS)scores,Coma Recovery Scale-Revised(CRS-R)scores,and Persistent Vegetative State(PVS)scores of two groups after intervention were significantly higher than those before intervention,and these indicators of observation group were significantly higher than them of control group after intervention,and the differences were significant(t=7.187,15.586,9.293,P<0.05),respectively.There were not significant differences in Glasgow Outcome Scale(GOS)scores and Activities of Daily Living(ADL)scores between two groups before intervention(P>0.05),and these scores of two groups were significantly increased after intervention,and these scores of observation group were significantly higher than them of control group after intervention,and the differences were significant(t=7.584,6.755,P<0.05).Additionally,the hospital stay duration and treatment costs of observation group were significantly less than those of control group,and the differences were significant(t=20.965,9.503,P<0.05).Conclusion:The intervention of AI rehabilitation system combines with a telemedicine platform on patients with long-term coma can enhance GCS,CRS-R,PVS,GOS and ADL scores,and reduce hospital stay duration and treatment cost.

This study aims to investigate the medication rules of patented traditional Chinese medi-cine(TCM)compound formulas and molecular mechanisms of core drugs for treating sepsis using data mining and network pharmacology approaches.In the present study,we first searched the PubMed database,Web of Science database,and the China National Knowledge Infrastructure(CNKI)since the establishment of the library to April 30,2024 for the relevant literature on the treatment of sepsis by traditional Chinese medicine.The prescriptions were then statistically ana-lyzed for drug frequency and association analysis to obtain the core drugs.Then we screened the ef-fective active ingredients of the core drugs by TCMSP and other database platforms,obtained sep-sis-related genes in GeneCards and other databases,and statistically intersected targets,and predic-ted the mechanism of action of the core TCMs by subjecting the intersected targets to PPI analy-sis,GO function and KEGG pathway enrichment analysis.Finally,the relationship between key tar-gets and herbal components was examined in reverse by molecular docking method.The results showed that 64 compound formulas were obtained,with a total of 150 Chinese medicines,which were mostly sweet in taste,cold in nature,and belonged to the spleen,stomach and intestinal me-ridians.According to the association rules,the core drugs were identified as"mirabilite-peach ker-nel-rheum officinale".There were 79 intersecting targets between the core drugs and sepsis,with core targets such as IL-1β,EGFR and SRC.MAPK,TNF,IL-17 and other signaling pathways are involved to mediate inflammatory responses,apoptosis and other biological processes to exert ther-apeutic effects on sepsis.The molecular docking results indicated that the docking activity of the key targets with the main components of the drug,and sennoside E_qt has the lowest binding ener-gy and the best docking activity with SRC.In conclusion,this study showed that the prescription of Chinese medicine for sepsis is mostly based on tonifying the spleen and clearing heat.The mecha-nism of action of the core drug"mirabilite-peach kernel-rheum officinale"in the treatment of sep-sis is multilevel and multifaceted,which provides a certain theoretical basis for the treatment of sepsis by traditional Chinese medicine.

Objective:To explore the potential categories of symptom characteristics of early breast cancer patients undergoing postoperative chemotherapy, analyze the differences of symptoms among different categories of patients, and compare their quality of life according to different categories.Methods:This was a cross-sectional study. From January to June 2023, 240 patients with early breast cancer who received chemotherapy after surgery in General Hospital of Ningxia Medical University were selected by convenience sampling. They were investigated by general information questionnaire, Memory Symptom Assessment Scale, and Functional Assessment of Caner Therapy-Breast Cancer. Mplus 8.3 was used to carry out potential profile analysis and identify the potential categories of symptom characteristics of early breast cancer patients undergoing postoperative chemotherapy. Binary Logistic regression analysis was used to determine the influencing factors of symptom characteristics. SPSS 26.0 software was used to compare the differences in quality of life scores of patients undergoing postoperative chemotherapy for different categories of early breast cancer.Results:Totally 233 valid questionnaires were ultimately collected, with an age of 50.85 ± 8.09. There were two potential categories of postoperative chemotherapy patients with early breast cancer: low symptom troubled group (159 cases, 68.2%) and high symptom troubled group (74 cases, 31.8%). The quality of life score of the high symptom distress group was (76.84 ± 13.15) points, which was significantly lower than (89.56 ± 11.29) points of the low symptom distress group, and the difference was statistically significant ( t=7.18, P<0.01). Logistic regression analysis showed that patients with early breast cancer who had financial burden after postoperative chemotherapy were more likely to belong to the group with high symptoms [ OR (95% CI) was 3.028 (1.434-6.394), P<0.01]. Postoperative chemotherapy patients with early breast cancer who had satisfactory sleep at night are more likely to belong to the group with low symptoms [ OR(95% CI) was 0.446 (0.217-0.920), P<0.05]. Conclusions:There is population heterogeneity in the symptom characteristics of patients with early breast cancer undergoing postoperative chemotherapy. and economic burden and night sleep are the influencing factors of symptom distress categories of breast cancer patients. It is suggested that medical staff should give individualized and targeted intervention measures centered on patients′ needs according to different types of population characteristics, so as to reduce the symptom burden and improve their quality of life.

This study aims to investigate the medication rules of patented traditional Chinese medi-cine(TCM)compound formulas and molecular mechanisms of core drugs for treating sepsis using data mining and network pharmacology approaches.In the present study,we first searched the PubMed database,Web of Science database,and the China National Knowledge Infrastructure(CNKI)since the establishment of the library to April 30,2024 for the relevant literature on the treatment of sepsis by traditional Chinese medicine.The prescriptions were then statistically ana-lyzed for drug frequency and association analysis to obtain the core drugs.Then we screened the ef-fective active ingredients of the core drugs by TCMSP and other database platforms,obtained sep-sis-related genes in GeneCards and other databases,and statistically intersected targets,and predic-ted the mechanism of action of the core TCMs by subjecting the intersected targets to PPI analy-sis,GO function and KEGG pathway enrichment analysis.Finally,the relationship between key tar-gets and herbal components was examined in reverse by molecular docking method.The results showed that 64 compound formulas were obtained,with a total of 150 Chinese medicines,which were mostly sweet in taste,cold in nature,and belonged to the spleen,stomach and intestinal me-ridians.According to the association rules,the core drugs were identified as"mirabilite-peach ker-nel-rheum officinale".There were 79 intersecting targets between the core drugs and sepsis,with core targets such as IL-1β,EGFR and SRC.MAPK,TNF,IL-17 and other signaling pathways are involved to mediate inflammatory responses,apoptosis and other biological processes to exert ther-apeutic effects on sepsis.The molecular docking results indicated that the docking activity of the key targets with the main components of the drug,and sennoside E_qt has the lowest binding ener-gy and the best docking activity with SRC.In conclusion,this study showed that the prescription of Chinese medicine for sepsis is mostly based on tonifying the spleen and clearing heat.The mecha-nism of action of the core drug"mirabilite-peach kernel-rheum officinale"in the treatment of sep-sis is multilevel and multifaceted,which provides a certain theoretical basis for the treatment of sepsis by traditional Chinese medicine.

Objective To explore the time-varying pattern of potential symptoms in breast cancer patient before and after chemotherapy,and further analyze its influencing factors,aims to provide reference for clinical nursing practice.Methods 233 cases of breast cancer in a tertiary A hospital in Ningxia from June to October,2023 were selected as the research subjects.By the general information questionnaire and the Chinese version of Anderson Symptom Assessment Scale,the potential change of symptoms of breast cancer patients undergoing chemotherapy 1-3 days before the first chemotherapy(T1,233 cases)and 7-14 days after the third or fourth chemotherapy(T2,225 cases)was analyzed.Results 225 cases of breast cancer patients completed 2 surveys,and their symptom characteristics before and after chemotherapy can be divided into 2 categories:a high symptom troubled group and a low symptom troubled group.The high-symptom troubled group has strong stability,and the probability of maintaining the original group is 85.20％,while the low-symptom troubled group is more inclined to change to the high-symptom troubled group,and the transition probability is 26.60％.Logistic regression analysis showed that the mass was located on the left side,and the patients who obtained disease knowledge mainly through the Internet were more likely to change from the high symptom troubled group to the low symptom troubled group,while the patients who were employed,with unsatisfactory sleep at night,and never exercised were more likely to change from the low symptom troubled group to the high symptom troubled group.Conclusion The symptoms of breast cancer patients before and after chemotherapy are heterogeneous.Patients who are on the job,have unsatisfied sleep at night and never exercise are more likely to change from the low-symptom troubled group to the high-symptom troubled group,which suggests that medical staff should identify potential high-risk groups at an early stage,and make full use of the predictive function of symptom characteristics to carry out individualized management based on the dynamic monitoring of symptoms according to different types of population characteristics,so as to reduce the burden of symptoms and improve their quality of life.

Objective:To explore the potential categories of symptom characteristics of early breast cancer patients undergoing postoperative chemotherapy, analyze the differences of symptoms among different categories of patients, and compare their quality of life according to different categories.Methods:This was a cross-sectional study. From January to June 2023, 240 patients with early breast cancer who received chemotherapy after surgery in General Hospital of Ningxia Medical University were selected by convenience sampling. They were investigated by general information questionnaire, Memory Symptom Assessment Scale, and Functional Assessment of Caner Therapy-Breast Cancer. Mplus 8.3 was used to carry out potential profile analysis and identify the potential categories of symptom characteristics of early breast cancer patients undergoing postoperative chemotherapy. Binary Logistic regression analysis was used to determine the influencing factors of symptom characteristics. SPSS 26.0 software was used to compare the differences in quality of life scores of patients undergoing postoperative chemotherapy for different categories of early breast cancer.Results:Totally 233 valid questionnaires were ultimately collected, with an age of 50.85 ± 8.09. There were two potential categories of postoperative chemotherapy patients with early breast cancer: low symptom troubled group (159 cases, 68.2%) and high symptom troubled group (74 cases, 31.8%). The quality of life score of the high symptom distress group was (76.84 ± 13.15) points, which was significantly lower than (89.56 ± 11.29) points of the low symptom distress group, and the difference was statistically significant ( t=7.18, P<0.01). Logistic regression analysis showed that patients with early breast cancer who had financial burden after postoperative chemotherapy were more likely to belong to the group with high symptoms [ OR (95% CI) was 3.028 (1.434-6.394), P<0.01]. Postoperative chemotherapy patients with early breast cancer who had satisfactory sleep at night are more likely to belong to the group with low symptoms [ OR(95% CI) was 0.446 (0.217-0.920), P<0.05]. Conclusions:There is population heterogeneity in the symptom characteristics of patients with early breast cancer undergoing postoperative chemotherapy. and economic burden and night sleep are the influencing factors of symptom distress categories of breast cancer patients. It is suggested that medical staff should give individualized and targeted intervention measures centered on patients′ needs according to different types of population characteristics, so as to reduce the symptom burden and improve their quality of life.

Objective:To analyze the applied effect of artificial intelligence(AI)rehabilitation system combined with telemedicine platform in individualized rehabilitation treatment for patients with long-term coma,so as to realize individual management for them.Methods:An AI rehabilitation system that aimed to patients with long-term coma was designed by integrating data of multimodal sensors included inertial sensor,image sensor and bioelectric sensor.A telemedicine platform,which included seven modules(patient management,consultation management,video communication,data transmission,electronic medical records,cost management and system maintenance),was designed by using a browser/server(B/S)architecture.The changes of patients'condition were followed up,and the full process of the management for rehabilitation treatment and the individualization of treatment plan were realized.A total of 60 inpatients whose coma duration exceeded 28 days were selected from the Coma Awakening Center of Dongguan Shipai Hospital between October 1,2021 and September 30,2022.They were randomly divided into control group(n=30)and observation group(n=30)by random number table.The control group received physical therapy and rehabilitation training based on evaluation results of rehabilitation,while the observation group adopted AI rehabilitation system combined with the telemedicine platform to conduct intervention.The consciousness levels,quality of life,hospital stay duration and treatment costs of two group were compared after intervention.Results:The Glasgow Coma Scale(GCS)scores,Coma Recovery Scale-Revised(CRS-R)scores,and Persistent Vegetative State(PVS)scores of two groups after intervention were significantly higher than those before intervention,and these indicators of observation group were significantly higher than them of control group after intervention,and the differences were significant(t=7.187,15.586,9.293,P<0.05),respectively.There were not significant differences in Glasgow Outcome Scale(GOS)scores and Activities of Daily Living(ADL)scores between two groups before intervention(P>0.05),and these scores of two groups were significantly increased after intervention,and these scores of observation group were significantly higher than them of control group after intervention,and the differences were significant(t=7.584,6.755,P<0.05).Additionally,the hospital stay duration and treatment costs of observation group were significantly less than those of control group,and the differences were significant(t=20.965,9.503,P<0.05).Conclusion:The intervention of AI rehabilitation system combines with a telemedicine platform on patients with long-term coma can enhance GCS,CRS-R,PVS,GOS and ADL scores,and reduce hospital stay duration and treatment cost.

Objective To study the serum laminin γ 2 monomer(LG2m),human circulating Gastrin(hPG80)in patients with hepatocellular carcinoma(HCC)and their clinical value.Methods 128 HCC patients admitted to the First People's Hospital of Shuangliu District from January 2016 to January 2018 were selected as the HCC group,70 patients with benign liver lesions diagnosed and treated at the same time were selected as the benign lesion group,and 70 healthy individuals who underwent physical examinations during the same time were selected as the control group.Use enzyme-linked immunosorbent assay to detect serum LG2m and hPG80 levels.The evaluation value of serum LG2m and hPG80 in predicting the prognosis of HCC patients were analyzed by receiver operating characteristic curve.Kaplan-Meier survival analysis was used to compare the survival prognosis of HCC patients with different serum LG2m and hPG80 levels.COX regression analysis was used to analyze the prognostic factors of HCC patients.Results The levels of serum LG2m(28.14±3.10 ng/L),hPG80(84.83±11.39 ng/L)in the HCC group were higher than those in the benign lesion group(9.18±1.74 ng/L,25.10±4.11 ng/L)and the control group(8.24±1.65 ng/L,23.15±3.26 ng/L),and the differences were statistically significant(t=68.240～76.635,all P＜0.05).The levels of serum LG2m and hPG80 in patients with TNM stage III,low differentiation degree,serum AFP＞400 μg/L were higher than those in TNM stage I to II,high differentiation,AFP≤400 μg/L,the differences were statistically significant(t=3.216～13.552,all P＜0.05).The area under the curve(95%CI)of the combined evaluation of serum LG2m and hPG80 for the prognosis of HCC patients was 0.934(0.889～0.961),which was greater than the single indicator of 0.813(0.774～0.849)and 0.896(0.840～0.937).The overall 5-year survival rates of HCC patients with high and low serum LG2m expression were 33.33%(21/63)and 67.69%(44/65),respectively.Compared with HCC patients with low expression of serum LG2m,HCC patients with high expression of serum LG2m had a lower 5-year cumulative survival rate(Log-Rankχ2=19.522,P＜0.05).The overall 5-year survival rates of HCC patients with high and low serum hPG80 expression were 35.48%(22/62)and 65.15%(43/66),respectively.Compared with HCC patients with low serum hPG80 expression,HCC patients with high serum hPG80 expression had a lower 5-year cumulative survival rate(Log-Rankχ2=12.546,P＜0.05).TNM stage III(OR=1.487,P＜0.05),low differentiation degree(OR=1.611,P＜0.05),serum AFP≥400μg/L(OR=1.416,P＜0.05),high expression of serum LG2m(OR=1.838,P＜0.05),and high expression of hPG80(OR=1.735,P＜0.05)were independent risk factors for poor prognosis in HCC patients.Conclusion The serum levels of LG2m and hPG80 in HCC patients increase,which are related to TNM staging,tumor differentiation,and serum AFP levels.They are serum biomarkers for evaluating the survival and prognosis of HCC patients.

A 66-year-old male patient intermittently drank soading water of Tephroseris kirilowii by himself to alleviate skin itching caused by scabies. After nearly 2 years, he developed symptoms of abdominal distension, abdominal pain, poor appetite, and yellow urine. Laboratory tests showed total bilirubin (TBil) 158.2 μmol/L, direct bilirubin (DBil) 73.5 μmol/L, alanine aminotransferase (ALT) 96 U/L, aspartate aminotransferase (AST) 131 U/L, cholinesterase 1.40 kU/L, and international normalized ratio (INR) 1.7. Magnetic resonance imaging examination of upper abdomen showed consistent performance with the manifestation of hepatic sinusoidal obstruction syndrome. After excluding other causes, it was considered that it was caused by Tephroseris kirilowii. Supportive treatments such as anti-infection, liver protection, diuresis, nutritional support, anticoagulation, and reducing portal vein pressure were given. But the patient′s symptoms continue to worsen, with intermittent complications such as hepatic encephalopathy and gastrointestinal bleeding. After 67 days of treatments, laboratory tests showed TBil 192.0 μmol/L, DBil 96.7 μmol/L, ALT 118 U/L, AST 193 U/L, and cholinesterase 0.72 kU/L. The patient was discharged upon request from himself and the families, and died 5 days later.