p21 (encoded by the CDKN1A gene) is a critical cell cycle regulatory protein endowed with versatile biological functions. In various sex hormone-related cancers, p21 exhibits a paradoxical dual role, capable of both inhibiting tumorigenesis and promoting cancer progression, exerting dual, often opposing, effects on cellular fate that are dictated by the specific context. The clinical targeting of p21 remains elusive, largely due to its functionally pleiotropic and context-dependent nature within intricate regulatory networks. During the initial, hormone-dependent phase of cancers like breast and prostate cancer, p21 expression and activity are largely governed by the transcriptional programs of estrogen or androgen receptor signaling. This hormonal regulation contributes to the control of tumor cell proliferation and underpins the initial efficacy of endocrine therapies. In contrast, as these diseases advance to late stages or evolve into non-hormone-dependent subtypes—exemplified by castration-resistant prostate cancer (CRPC) and specific forms of triple-negative breast cancer (TNBC)—these conventional hormonal control mechanisms often become dysfunctional or are entirely bypassed. This fundamental transition creates a critical therapeutic void, highlighting the urgent need to identify and exploit alternative molecular pathways to effectively target p21’s function. Promising strategies may include the precise modulation of its upstream transcriptional regulators, downstream effector proteins, or the intersecting parallel signaling networks that critically influence its activity. This review provides a systematic synthesis of the intricate and interconnected mechanisms that underpin the dual effects of p21 in sex hormone-related tumors. These mechanisms are categorized into three core, interrelated functional domains. (1) cell cycle regulation: p21 executes its canonical tumor-suppressive role by binding to and inhibiting cyclin-dependent kinases (CDKs) and by directly interacting with proliferating cell nuclear antigen (PCNA), thereby inducing cell cycle arrest, predominantly at the G1/S checkpoint; (2) apoptosis modulation: p21 exerts a highly context-dependent influence on programmed cell death, functioning either as a pro-apoptotic agent under severe genotoxic stress or as a pro-survival factor by inhibiting apoptosis through interactions with proteins like Bcl-2; (3) hormonal and signaling crosstalk: p21 is an integral node within broader cellular networks, engaging in direct physical interactions with hormone receptors(e.g., AR, ER) and participating in complex feedback loops with key oncogenic pathways, including PI3K/AKT, MAPK/ERK, and p53. Critically, the role of p21 is not static but highly dynamic. It can undergo a functional switch from tumor-suppressive to tumor-promoting in response to therapeutic pressures, metabolic alterations, or evolving tumor microenvironment cues. These adaptive shifts are frequently implicated in the development of therapy resistance and disease recurrence, particularly in advanced, hormone-resistant cancers. By synthesizing these insights, this review aims to establish a coherent theoretical framework to guide the future development of novel therapeutic strategies that target the p21 pathway. It underscores the necessity of moving beyond a simplistic, binary view of p21 and emphasizes the forthcoming challenges, such as the discovery of reliable biomarkers to predict its functional state and the rational design of context-specific pharmacological modulators to selectively harness its therapeutic potential.

Objective:To investigate the clinical demand for subcutaneous immunotherapy (SCIT) with pet allergens and explore the sensitization characteristics of patients undergoing pet SCIT.Methods:A cross-sectional retrospective analysis was conducted on patients diagnosed with pet allergies and treated with pet allergen SCIT in our outpatient clinic from January 2019 to December 2023. Patients were categorized into three groups based on the type of SCIT received: single-cat SCIT group, single-dog SCIT group, and combined cat-dog SCIT group.Results:A total of 931 patients were included, the age range was 5-65 years (median age of 30 years), with 283 male and 648 female. Among them, 67.7%( n=630) received single-cat SCIT, 10.9% ( n=102)received single-dog SCIT, and 21.4% ( n=199) received combined cat-dog SCIT. The number of patients receiving pet allergen SCIT increased annually. Patients in the single-dog SCIT group were significantly older than those in the other two groups ( H=41.329, P<0.001) and had a lower prevalence of allergic rhinitis (91.2% vs. 96.5% and 98.5%; χ2=10.400, P=0.006). In the combined cat-dog SCIT group, the allergy rate to mold allergens was significantly higher than in the single-cat SCIT group (12.6% vs. 4.9%, χ2=13.965, P=0.001). In the single-dog SCIT group, the allergy rate to spring pollen allergens was significantly higher than in the other two groups ( χ2=15.731, P<0.001), and the allergy rate to autumn pollen allergens was significantly higher than in the single-cat SCIT group ( χ2=13.459, P=0.001). There was no significant difference in the dust mite allergy rate among the three groups( χ2=4.117, P=0.129). In the single-dog SCIT group, patients with asthma were significantly older than those without asthma (41.2 vs. 35.2 years old, t=-2.073, P=0.041). In both the single-cat and single-dog SCIT groups, the proportion of allergic rhinitis in the asthma group(91.2%,78.3%) was significantly lower than that in the non-asthma group(97.4%,94.9%) ( χ2=8.863,6.158; P=0.008,0.026). In the single-cat SCIT group, non-asthmatic patients were significantly more likely to receive SCIT combined with spring pollen allergens compared to asthmatic patients (23.9% vs. 11.0%, χ2=7.586, P=0.006). Conclusions:The demand for pet allergen SCIT has steadily increased over the years, with a predominance of female patients. Sensitization profiles varied among patients receiving SCIT for different pet allergens. This study comprehensively elucidates the clinical demand and sensitization characteristics of patients undergoing pet allergen SCIT, providing valuable reference data for clinical diagnosis and treatment.

ObjectiveThis paper proposes a novel real-time bedside pulmonary ventilation monitoring method for the diagnosis of chronic obstructive pulmonary disease (COPD), based on electrical impedance tomography (EIT). Four indicators—center of ventilation (CoV), global inhomogeneity index (GI), regional ventilation delay inhomogeneity (RVDI), and the ratio of forced expiratory volume in one second to forced vital capacity (FEV₁/FVC)—are calculated to enable the spatiotemporal assessment of COPD. MethodsA simulation of the respiratory cycles of COPD patients was first conducted, revealing significant differences in certain indicators compared to healthy individuals. The effectiveness of these indicators was then validated through experiments. A total of 93 subjects underwent multiple pulmonary function tests (PFTs) alongside simultaneous EIT measurements. Ventilation heterogeneity under different breathing patterns—including forced exhalation, forced inhalation, and quiet tidal breathing—was compared. EIT images and related indicators were analyzed to distinguish healthy individuals across different age groups from COPD patients. ResultsSimulation results demonstrated significant differences in CoV, GI, FEV₁/FVC, and RVDI between COPD patients and healthy individuals. Experimental findings indicated that, in terms of spatial heterogeneity, the GI values of COPD patients were significantly higher than those of the other two groups, while no significant differences were observed among healthy individuals. Regarding temporal heterogeneity, COPD patients exhibited significantly higher RVDI values than the other groups during both quiet breathing and forced inhalation. Moreover, during forced exhalation, the distribution of FEV₁/FVC values further highlighted the temporal delay heterogeneity of regional lung function in COPD patients, distinguishing them from healthy individuals of various ages. ConclusionEIT technology effectively reveals the spatiotemporal heterogeneity of regional lung function, which holds great promise for the diagnosis and management of COPD.

[Objective] To analyse and predict the tendencies of using erythrocyte blood in Changsha based on the autoregressive integrated moving average (ARIMA) model, long short-term memory (LSTM) and ARIMA-LSTM combination model, so as to provide reliable basis for designing a feasible and effective blood inventory management strategy. [Methods] The data of erythrocyte usage from hospitals in Changsha between January 2012 and December 2023 were collected, and ARIMA model, LSTM model and ARIMA-LSTM combination model were established. The actual erythrocyte consumption from January to May 2024 were used to assess and verify the prediction effect of the models. The extrapolation prediction accuracy of the models were tested using two evaluation indicators: mean absolute percentage error (MAPE) and root mean square error (RMSE), and then the prediction performance of the model was compared. [Results] The RMSE of LSTM model, optimal model ARIMA(1,1,1)(1,1,1)12 and ARIMA-LSTM combination model were respectively 5 206.66, 3 096.43 and 2 745.75, and the MAPE were 18.78%,11.54% and 9.76% respectively, which indicated that the ARIMA-LSTM combination model was more accurate than the ARIMA model and LSTM model, and the prediction results was basically consistent with the actual situation. [Conclusion] The ARIMA-LSTM model can better predict the clinical erythrocyte consumption in Changsha in the short term.

Objective To investigate the expression of serum long non-coding RNA X-inactive specific transcript(lncRNA XIST)and microRNA-126-3p(miR-126-3p)in patients with non-small cell lung cancer(NSCLC),and their relationship with recurrence after radical surgery.Methods A total of 108 NSCLC patients who underwent radical surgery and were admitted to General Hospital of Southern Theater Command of the People's Liberation Army of China from February 2019 to October 2020 were selected as the NSCLC group,and 52 healthy volunteers who underwent physical examination in this hospital were selected as the control group.qRT-PCR method was used to detect the relative expression levels of serum lncRNA XIST and miR-126-3p.Pearson method was used to analyze the correlation between serum lncRNA XIST and miR-126-3p expression.Logistic regression analysis was used to analyze the influencing factors of postoperative recurrence in NSCLC patients.Receiver operating characteristic(ROC)curve was used to evaluate the predictive value of serum lncRNA XIST and miR-126-3p on postoperative recurrence in patients.Results The expression level of serum lncRNA XIST in the NSCLC group was higher than that in the control group(P<0.05),while the expression level of miR-126-3p was lower than that in the control group(P<0.05).The expression levels of serum lncRNA XIST and miR-126-3p were related to TNM staging and lymph node metastasis(P<0.05).Bioinformatics website predicted that there was a targeted binding site between lncRNA XIST and miR-126-3p,and serum lncRNA XIST was negatively correlated with miR-126-3p expression(r=-0.579,P<0.05).Compared with the non-recurrent group,the expression level of serum lncRNA XIST in the recurrent group increased(P<0.05),while the expression level of miR-126-3p in the recurrent group decreased(P<0.05).Logistic regression analysis results showed that lncRNA XIST,miR-126-3p,lymph node metastasis,and TNM staging were the influencing factors for postoperative recurrence in NSCLC patients(P<0.05).The area under the curve(AUC)of serum lncRNA XIST,miR-126-3p,and the combination of the two in prediction of postoperative recurrence in NSCLC patients were 0.750,0.886,and 0.933,respectively,the combined prediction of the two was superior to individual prediction(Zcombination vs.lncRNA XIST=4.076,Zcombination vs.miR-126-3p=2.065,P<0.05).Conclusion The expression of serum lncRNA XIST is increased and miR-126-3p is decreased in NSCLC patients,both of which have certain predictive value for recurrence after radical surgery in patients.

In order to establish a simple,sensitive and specific diagnostic method for the simultane-ous detection of Mycoplasma hyorhinis(Mhr)and Mycoplasma hyopneumoniae(Mhp)in swine,specific primers and probes were designed using the Mhr p37 and Mhp p36 gene sequences as the target genes,and the dual LFD-RPA rapid test was established by screening the primers and probes,optimizing primer ratios and evaluating its effectiveness through the sensitivity,reproduc-ibility and clinical sample testing.The sensitivity,specificity,reproducibility and clinical samples were evaluated.The results showed that the established dual LFD-RPA assay could complete the amplification in 15 min at 39 ℃,and its optimal primer ratio was 1.6∶0.8,and the lowest detection limits were up to 3.63 and 3.60 copies/μL,respectively;the reproducibility was stable;and there was no cross-reactivity with Pasteurella multocida,Bordetella bronchiseptica,Haemophilus pa-rasuis,Actinobacillus pleuropneumoniae,Escherichia coli.The test successfully established a dual LFD-RPA assay,which can detect Mhr and Mhp simultaneously,and is simple,sensitive and spe-cific without relying on specialized equipment,and is suitable for carrying out on-site rapid diagno-sis of Mhr and Mhp.

Objective To screen genes associated with poor prognosis of colorectal cancer(CRC)through bioinformatics analysis.Methods The gene expression profiles of GSE74602,GSE110223,GSE113513 and GSE141174 were obtained from Gene Expression Omnibus(GEO)database,including samples from 65 CRC tissues and 65 normal tissues.Differentially expressed genes(DEGs)between CRC tissues and normal tissues were screened out by GEO2R tool and Venn software,and the consistent genes were extracted from DEGs by Venn software.A protein-protein interaction(PPI)network was constructed by the STRING database to identify key genes,which were analyzed by Kaplan-Meier Plotter and GEPIA.Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis was conducted on the 13 selected genes.Results There were 171 DEGs obtained from the four datasets,including 148 up-regulated genes and 23 down-regulated genes.Up-regulated DEGs were enriched in the redox processes,bicarbonate transport,digestion,ion trans-membrane transport,and one-carbon metabolism;and down-regulated DEGs were enriched in the positive regulation of cell proliferation.The survival curve analysis showed that 30 of the 87 genes were significantly associated with poor survival prognosis.GEPIA showed that 13 of the 30 genes were highly expressed in CRC tissues compared to normal tissues,among which MYC and FGFR3 markedly enriched in the CRC pathway.Conclusion This study identifies that MYC and FGFR3 are significantly up-regulated in CRC and closely associated with poor prognosis,suggesting that they may serve as potential prognostic markers and therapeutic targets for CRC patients.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

Objective To explore the abnormal expression of the MT-ND family in pan-cancers and its prognostic value.Methods Transcriptome expression and clinical data of 33 cancers were downloaded from the TCGA database,thereby analyzing the expression differences of the MT-ND family in tissuesof different types of cancers and normal tissues.The prognostic role of the MT-ND family in pan-cancers was explored by univariate Cox regression analysis and Kaplan-Meier survival analysis.Results The expression of the MT-ND family was upregulated in the kidney chromophobe,acute myeloid leukemia and thymoma,and downregulated in the remaining tumors.The expression of the MT-ND family was associated with the overall survival rate of different types of cancers.In addition,the MT-ND family were significantly correlated with the immune invasion subtypes,and were correlated with stromal cell invasion and tumor cell stemness to varying degrees.The expression of MT-ND4 was downregulated in brain lower grade glioma,which was a protective factor for prognosis;while the expression of MT-ND4 in thymoma was upregulated,which was a risk factor for prognosis.Conclusion Pan-cancer analysis has confirmed that the MT-ND family can predict the tumor prognosis,which provides new ideas and strategies for the precision treatment and prognostic management of cancer.