Linzhou,formerly known as Lin County,is the pioneer site for cancer prevention and control in China,established as early as 1959.For more than 60 years,the construction of cancer prevention and control system in Linzhou has been continuously improved,but in the face of the new situation of cancer prevention and control,the existing system has deficiencies in cancer registration,screening,treatment,scientific research,science popularization and other aspects.With the establishment of Linzhou Cancer Center,it has brought new opportunities and new mis-sions for Linzhou cancer prevention and control.Based on this,this paper puts forward a series of measures for the construction of Linzhou cancer prevention and control system,aiming to improve the Linzhou cancer prevention and control system and improve the prevention and control efficiency.

Objective:To investigate the effects of surgical timing on incidence of perioperative complications and postoperative 30-day mortality in elderly patients with hip fracture.Methods:The data were retrospectively analyzed of the 450 elderly patients with hip fracture who had been admitted to Department of Joint Surgery, Beijing Shijitan Hospital, Capital Medical University from January 2016 to December 2021. The patients were divided into 2 groups according to the time from admission to surgery. In the early surgery group of 143 cases [41 males and 102 females with an age of 82(75, 86) years], the time from admission to surgery was ≤ 48 hours. In the delayed surgery group of 307 cases [88 males and 219 females with an age of 83(77, 87) years], the time from admission to surgery was over 48 hours. The 2 groups were compared in terms of comorbidities, perioperative complications, death events within postoperative 30 days, ICU transfer rate and total length of hospital stay.Results:There was no significant difference in the preoperative general data like age and gender between the 2 groups, indicating comparability ( P>0.05). The proportions of patients with coronary atherosclerotic heart disease [30.0%(92/307)], a stroke history [19.9%(61/307)], abnormal heart function [55.4%(170/307)] and abnormal kidney function [24.4%(75/307)] in the delayed surgery group were significantly higher than those in the early surgery group [18.2%(26/143), 10.5% (15/143), 39.2%(56/143), and 12.6%(18/143)] ( P<0.05). The proportions of perioperative pulmonary infection [22.5% (69/307)] and urinary infection [21.2%(65/307)] in the delayed operation group were significantly higher than those in the early operation group [11.9%(17/143) and 11.2%(16/143)] ( P<0.05). The total hospital stay in the delayed operation group [18(14, 22) d] was significantly longer than that in the early operation group [14(10, 17) d] ( P<0.05). There was no significant difference in ICU transfer rate or postoperative 30-day mortality between the 2 groups ( P>0.05). Conclusion:For elderly patients with hip fracture, delayed surgery may increase the incidence of pulmonary infection and urinary infection, and extend their total hospital stay, but have no effect on the postoperative 30-day mortality.

The paper reports a 32-year-old female acute myeloid leukemia patient who developed graft-versus-host disease after paternal hematopoietic stem cell transplantation, which subsequently led to renal thrombotic microangiopathy. She subsequently required a kidney transplant from the same donor 5 years later due to renal failure. Considering that both the bone marrow and kidney were from the same donor and the recovery of renal function was favorable, immunosuppressive therapy was discontinued after a short course of anti-rejection treatment, with maintained stable kidney function. This case suggests that under the condition of high chimerism, allogeneic hematopoietic stem cell transplantation and kidney transplantation from the same donor can achieve immune tolerance, potentially improving solid organ transplantation success rate. The findings provide a novel therapeutic approach for solid organ transplantation following allogeneic hematopoietic stem cell transplantation.

Objective:To investigate whether intratumoral Gemella haemolysans(G.haemolysans)enhances the efficacy of neoadjuvant chemoimmunotherapy(NACI)in esophageal squamous cell carcinoma(ESCC)-bearing mice and the underlying mechanism.Methods:Twenty-five 4-week-old female C57BL/6 mice were randomized into five groups(n=5 per group):negative control(NC)group,chemo-therapy group,G.haemolysans+chemotherapy group,NACI group,and G.haemolysans+NACI group.A germ-free mouse model was established in each group by administering antibiotic cocktail for 2 weeks.On day 0,ESCC-bearing mouse models were built through subcutaneous inoculation of either murine esophageal cancer cell line AKR or G.haemolysans-AKR cells.On day 7 when tumors formed under the skin,drugs were injected into the abdomen thrice weekly.On day 28 when the treatments were finished,the mice were sacrificed to harvest their tumors,and then the tumors were fixed in 4%paraformaldehyde.We located and quantified G.haemolysans within the tumors through fluorescence in situ hybridization,and characterized immune cell composition in the tumor immune microen-vironment(TIME)of the mice treated with NACI through multiplex immunohistochemistry and flow cytometry.Results:G.haemolysans significantly strengthened the efficacy of NACI in ESCC(P<0.05),whereas no chemosensitizing effects were observed on chemo-therapy in ESCC-bearing mice.G.haemolysans significantly en-hanced natural killer(NK)cell infiltration within the TIME(P<0.01).Conclusion:G.haemolysans improves NACI efficacy in ESCC-bearing mice by increasing NK cell recruitment in the TIME.

Objective To conduct an analysis on objective data of tongue manifestations and complexions among college students with yang deficiency constitution and balanced constitution,thus to explore the correlation between yang deficiency constitution and the objective data of tongue manifestations and complexions among college students.Methods From August 2023 to January 2024,data collection was carried out in 325 cases of yang deficiency constitution(yang deficiency group)and 175 cases of balanced constitution(balanced group)from college students of Hunan University of Chinese Medicine,Central South University,Hunan Normal University,Hunan University and Changsha University of Science and Technology in Hunan Province.YM-MA-Ⅰ digital detection system for tongue manifestations and complexions of traditional Chinese medicine(TCM)was utilized for data collection and image analysis,and the differences in the Lab parameters of tongue color,tongue shape,tongue coating color,complexions,and lip color were compared between yang deficiency group and balanced group.Of the Lab parameters,letter"L"stands for luminance,which expresses the luminance from absolute black to absolute white,and takes the value of 0-100;letter"a"and letter"b"stand for two color channels,letter"a"represents the color from dark green to grey then to bright pink,and takes a value from-128 to 127,and letter"b"represents the color from bright blue to grey then to yellow,and also takes a value from-128 to 127.Results(1)The analysis of tongue manifestations showed that in comparison with the balanced group,enlarged tongue(72.62％),tooth-marked tongue(83.69％),and greasy coating(59.38％)were frequently seen in the yang deficiency group,and the differences were all statistically significant(P＜0.05 or P＜0.01).(2)The analysis of complexions showed that in comparison with the balanced group,lusterless complexion(79.08％)and pale lip(42.15％)were frequently seen in the yang deficiency group,with statistically significant differences(P＜0.01).(3)The yang deficiency group had higher L value of tongue color,L value of tongue coating color,L value of complexions,and L and b values of lip color than the balanced group,and the differences were all statistically significant(P＜0.05),indicating that the tongue color,complexions,and lip color of the yang deficiency group were all pale.Conclusion The objective data and image analysis of tongue manifestations and complexions can accurately identify the population of yang deficiency constitution from college students,and the results will provide approaches and references for the identification of other TCM constitutions from the population.

Objective To analyze the differences in bone serum protein between patients with osteoporosis accompanied by obstructive sleep apnea syndrome(OSAS)and those with osteoporosis only using proteomics.Methods A total of 80 osteoporosis patients who attended our hospital between June 2022 and June 2024 were enrolled.Based on their polysomnography results,the participants were divided into an OSAS and osteoporosis comorbidity(OSAS-osteoporosis)group(n=42)and an osteoporosis only group(n=38).Propensity score matching was applied to incorporate covariates in logistic regression so that the individual characteristics of the two groups of patients were generally balanced.Following the matching procedure,a final cohort of 20 matched pairs was obtained and subsequently utilized for further analysis.The mass spectrum was obtained using laser desorption ionization mass spectrometry.Principal component analysis(PCA)was performed to assess differences in metabolic patterns between groups.Partial least squares discriminant analysis(PLS-DA)and orthogonal PLS-DA(OPLS-DA)were employed for further data analysis.Variable importance in projection(VIP)scores of each substance were calculated with OPLS-DA to screen the metabolites showing inter-group differences.Heatmaps were generated to visualize metabolic profile differences between the OSAS-osteoporosis group and the osteoporosis group.Enrichment pathway analysis was conducted on the differential identified metabolites.Results After propensity score matching,individual characteristics between the groups were well balanced.Mass spectrometry revealed significant differences between the OSAS-osteoporosis and osteoporosis groups.In the PCA score plot,the separation trend of the two groups was not significant.The PLS-DA score plot showed a discernible separation trend,with R2 and Q2 lower than those of the corresponding results of the real model,confirming the reliability of the model.OPLS-DA showed that the total R2X of the model was 0.635,R2Y was 0.879,and O2Y was 0.728,showing obvious separation trends between the two groups.A total of 16 differential metabolites were identified,including stearyl-oleyl-glycerol phosphate choline,phosphate choline,L-histidine,erucamide,2'-deoxyuridine,1-palmitoyl glycerol,thymine,tyramine,L-pyroglutamic acid,L-glutamic acid,myristate,glycerol-3-phosphate,caprylic acid,pregnenolone,L-arginine,D-4-hydroxyphenylglycine,and isobutyric acid.Heatmaps showed significant differences in metabolic profiles between the OSAS-osteoporosis group and the osteoporosis group.Pathway enrichment analysis showed that 27 metabolic pathways were involved.27 metabolic pathways.Under the conditions of P<0.05 and pathway impact>0.2,the three most significant metabolic pathways identified included mainly alanine,aspartate,and glutamate metabolism,arginine biosynthesis,and histidine metabolism.Conclusion Significant differences were observed in the metabolic profiles between patients with both OSAS and osteoporosis and those with osteoporosis alone.

Objective To analyze relevant literature on the essence of traditional Chinese medicine syndromes using bibliometric methods;To understand the current research status and hotspots in this field;To provide references for relevant research.Methods Research literature about the essence of TCM syndromes was retrieved from CNKI,VIP,Wanfang Data and CBM from 1st Jan.1979 to 30th June 2024.CiteSpace 6.2 software was used to conduct visualization analysis on authors,institutions,keywords,etc.Results A total of 695 articles were included,with an overall upward trend in publication volume followed by stabilization.The authors who published more articles included Luo Ren(13 articles),Zhao Xiaoshan(13 articles),Li Zegeng(12 articles),etc.The institutions with more publications included Shandong University of Traditional Chinese Medicine(35 articles),Beijing University of Chinese Medicine(33 articles),Chengdu University of Traditional Chinese Medicine(26 articles),etc.Institutions were clustered regionally,and cooperation was mostly between TCM universities and their affiliated hospitals,with less cross regional communication.High frequency keywords included kidney yang deficiency syndrome,metabolomics,animal models,TCM syndrome types,coronary heart disease,lung qi deficiency syndrome,spleen qi deficiency syndrome,liver depression and spleen deficiency syndrome,etc;Keyword clustering covered aspects such as biomolecules and metabolism,TCM syndromes,pathology,disease models,and animal research.Conclusion Research in the field of the essence of TCM syndromes is gradually receiving more attention.Exploring the essence of TCM syndromes at the molecular level through techniques such as genomics,transcriptomics,metabolomics and proteomics is a research hotspot and trend in this field.

The clinical detection of paroxysmal atrial fibrillation(PAF)remains challenging due to its transient and stochastic characteristics,and existing dynamic mode decomposition methods have limitations in modal redundancy reduction and feature extraction when processing single-channel noisy electrocardiogram(ECG)signals.Therefore,a signal analysis method based on high-order dynamic mode decomposition is proposed.It captures high-order correlations within ECG signals through tensor decomposition techniques and decomposes complex signals into physically interpretable dynamic modes.A stability evaluation framework for signal subsystem is established based on modal interaction relationships.By incorporating quantitative indicators including proportion of modes reflecting system instability,modal distribution entropy,and eigenvalue spectrum divergence,a feature discrimination model for PAF is developed.Experimental validation using the MIT-BIH atrial fibrillation database reveals statistically significant differences(P<0.05)in stability-related features between PAF episodes and normal sinus rhythms.The classification model based on support vector machine achieves an average recognition accuracy of 96.15%.These results demonstrate that the proposed method can effectively analyze nonlinear dynamic characteristics in noisy single-lead ECG signals,thereby establishing a novel quantitative analytical framework for early detection and accurate diagnosis of PAF.

Linzhou,formerly known as Lin County,is the pioneer site for cancer prevention and control in China,established as early as 1959.For more than 60 years,the construction of cancer prevention and control system in Linzhou has been continuously improved,but in the face of the new situation of cancer prevention and control,the existing system has deficiencies in cancer registration,screening,treatment,scientific research,science popularization and other aspects.With the establishment of Linzhou Cancer Center,it has brought new opportunities and new mis-sions for Linzhou cancer prevention and control.Based on this,this paper puts forward a series of measures for the construction of Linzhou cancer prevention and control system,aiming to improve the Linzhou cancer prevention and control system and improve the prevention and control efficiency.

The clinical detection of paroxysmal atrial fibrillation(PAF)remains challenging due to its transient and stochastic characteristics,and existing dynamic mode decomposition methods have limitations in modal redundancy reduction and feature extraction when processing single-channel noisy electrocardiogram(ECG)signals.Therefore,a signal analysis method based on high-order dynamic mode decomposition is proposed.It captures high-order correlations within ECG signals through tensor decomposition techniques and decomposes complex signals into physically interpretable dynamic modes.A stability evaluation framework for signal subsystem is established based on modal interaction relationships.By incorporating quantitative indicators including proportion of modes reflecting system instability,modal distribution entropy,and eigenvalue spectrum divergence,a feature discrimination model for PAF is developed.Experimental validation using the MIT-BIH atrial fibrillation database reveals statistically significant differences(P<0.05)in stability-related features between PAF episodes and normal sinus rhythms.The classification model based on support vector machine achieves an average recognition accuracy of 96.15%.These results demonstrate that the proposed method can effectively analyze nonlinear dynamic characteristics in noisy single-lead ECG signals,thereby establishing a novel quantitative analytical framework for early detection and accurate diagnosis of PAF.