ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

AIM To prepare anisamide-modified ursolic acid self-assembled nanoparticles,and to evaluate their anti-drug resistance effect of enzalutamide on prostate cancer.METHODS Nanoparticle precipitation method was adopted in the preparation of anisamide-modified and non-anisamide-modified self-assembled nanoparticles,respectively,after which the particle size,Zeta potential and encapsulation efficiency were determined,and the morphology was observed under transmission electron microscope.The intake of cancer-associated fibroblasts(CAFs)was investigated,after which the model for enzalutamide resistance in prostate cancer was established,CCK8 assay was applied to analyzing the sensitization effect of self-assembled nanoparticles on enzalutamide,and Western blot was used for the detection of NRG1,HER3,AKT expressions.RESULTS The anisamide-modified self-assembled nanoparticles demonstrated the average particle size,Zeta potential and encapsulation efficiency of(195.13±8.06)nm,(-29.07±0.55)mV and(94.58±0.84)％,respectively.CAFs displayed higher intake in the anisamide-modified self-assembled nanoparticles than that in the non-modified preparation and free Cy5(P＜0.05).Meanwhile,anisamide-modified self-assembled nanoparticles were able to inhibit enzalutamide resistance caused by CAFs,reduce NRG1 expression on CAFs,and anisamide-modified self-assembled nanoparticles-treated conditioned medium of CAFs could reduce HER3 and AKT expression on LNCaP cells(P＜0.05,P＜0.01).CONCLUSION Anisamide-modified ursolic acid self-assembled nanoparticles can enhance the targeting of CAFs,alleviate the drug resistance effect of enzalutamide on prostate cancer caused by CAFs,and reduce NRG1 expression in CAFs.

AIM To prepare anisamide-modified ursolic acid self-assembled nanoparticles,and to evaluate their anti-drug resistance effect of enzalutamide on prostate cancer.METHODS Nanoparticle precipitation method was adopted in the preparation of anisamide-modified and non-anisamide-modified self-assembled nanoparticles,respectively,after which the particle size,Zeta potential and encapsulation efficiency were determined,and the morphology was observed under transmission electron microscope.The intake of cancer-associated fibroblasts(CAFs)was investigated,after which the model for enzalutamide resistance in prostate cancer was established,CCK8 assay was applied to analyzing the sensitization effect of self-assembled nanoparticles on enzalutamide,and Western blot was used for the detection of NRG1,HER3,AKT expressions.RESULTS The anisamide-modified self-assembled nanoparticles demonstrated the average particle size,Zeta potential and encapsulation efficiency of(195.13±8.06)nm,(-29.07±0.55)mV and(94.58±0.84)％,respectively.CAFs displayed higher intake in the anisamide-modified self-assembled nanoparticles than that in the non-modified preparation and free Cy5(P＜0.05).Meanwhile,anisamide-modified self-assembled nanoparticles were able to inhibit enzalutamide resistance caused by CAFs,reduce NRG1 expression on CAFs,and anisamide-modified self-assembled nanoparticles-treated conditioned medium of CAFs could reduce HER3 and AKT expression on LNCaP cells(P＜0.05,P＜0.01).CONCLUSION Anisamide-modified ursolic acid self-assembled nanoparticles can enhance the targeting of CAFs,alleviate the drug resistance effect of enzalutamide on prostate cancer caused by CAFs,and reduce NRG1 expression in CAFs.

Aim To investigate the protective effect of Gualou Guizhi granules(GLGZG)on neuronal injury induced by LPS-activated microglia based on Notch signaling pathway.Methods LPS-activated microglia were co-cultured with neurons to construct neuron inju-ry models,and the cells were divided into the control group,model group,Notch inhibitor(DAPT)group,GLGZG(50,100,200 mg·L-1)group,DAPT+100 mg·L-1GLGZG group.After intervention,the activity of HT22 cells was detected by CCK-8 method,and rel-ative mRNA expression was detected by real-time PCR.The relative protein expression was detected by Western blot.Results Compared with the model group,after GLGZG intervention,the cell activity was significantly improved,GLGZG decreased IL-6,IL-12,Bax,Notch 1,caspase-3,Delta-1,NICD,RBPSUH,HES1 expression,and increased Bcl-2 expression(P＜0.05).Compared with the model group,the NICD,RBPSUH and HES1 mRNA and protein expressions significantly decreased after DAPT treatment(P＜0.05),and there was no superposition effect with GLG-ZG.Conclusion GLGZG may play a neuroprotective role by inhibiting inflammatory factors and apoptosis,and inhibiting Notch signaling pathway.

Aim To infer novel therapeutic and phar-macological targets related to lung cancer treatment through multiomics approaches,so as to provide new directions for developing more personalized and effec-tive treatment strategies.Methods Genome-wide as-sociation study(GWAS)data analysis,pan-cancer,single-cell,transcriptomics,and protein-protein interac-tion analysis were employed in this study.Results We analyzed biomarkers and therapeutic targets associ-ated with lung cancer.The study identified key bio-markers closely related to lung cancer progression and explored the interrelationships between these biomark-ers and viral infections.According to KEGG pathway annotation,the number of genes related to metabolic processes increased significantly.In particular,metab-olites such as alanine and isoleucine emerged as pivotal factors in therapeutic interventions.The IgD+CD24+and IgD+CD24-B cell subsets were identified as cen-tral elements in immune evasion and treatment re-sponse.Concurrently,the Lachnospiraceae and Prevo-tella were shown to modulate host immune responses and the tumor microenvironment by regulating short-chain fatty acid levels,thereby opening novel avenues for cancer research.Conclusions Through mul-tiomics analysis combined with transcriptomics and pro-teomics analysis,we identify several potential therapeu-tic targets for lung cancer,providing key insights for developing novel treatment strategies.

Sepsis is a life-threatening organ dysfunction disease caused by a dysregulated host response to infection.It has com-plex pathophysiological changes,and in severe cases,it can rap-idly develop into septic shock and multiple organ dysfunction or multiple organ failure.At present,the pathological mechanism of sepsis and its induced organ dysfunction is complex and the in-fluencing factors are numerous.So far,there is still a lack of specific and effective treatment strategies.RNA modify-N6-methyladenosine(m6 A)is one of the most common post-tran-scriptional modifications on eukaryotic RNAs.It is involved in the regulation of the occurrence and development of a variety of inflammatory diseases,including sepsis,and even multiple organ dysfunction induced by sepsis by affecting the metabolism of RNAs.It includes cardiac dysfunction,acute lung injury(ALI)and acute kidney injury(AKI).Therefore,this article will dis-cuss the effect of m6A modification on the function of immune cells,and its important role in sepsis and its induced multiple or-gan dysfunction diseases by regulating inflammatory signals,py-roptosis,mitochondrial damage and ferroptosis.This will provide new therapeutic targets and strategies for the clinical prevention and treatment of sepsis and its induced multiple organ dysfunc-tion diseases.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective To investigate the effect of tissue-resident memory T cells(TRM)on imiquimod-induced psoriatic-like skin lesions in mice,and to elucidate the underlying mechanisms of TRM involvement in this process.Methods Forty female BALB/c mice were procured and randomly allocated into four groups:ten in the blank control group,and thirty for the establishment of a psoriasis mouse model.Following successful modeling,the thirty mice were further randomized into three groups:the model control group,the methotrexate-treated group,and the imiquimod-treated group,with ten mice in each group.Mice in the blank control group and model control group were uniformly treated with Vaseline for intervention.The methotrexate group and the imiquimod group were treated with 62.5mg of 5％imiquimod cream.The methotrexate group was administered by gavage at a dose of 1 mg/kg,and the gavage volume of each group was 10 mL/kg.The model control group,blank group and imiquimod group were gavaged with the same volume of normal saline.Treatment was conducted over six consecutive days.Subsequently,comparisons were made across groups regarding the psoriasis area and severity index(PASI),histopathological findings,inflammatory cytokine levels,and TRM cell levels.Results(1)The imiquimod group exhibited signifi-cantly lower scores for erythema(2.54±0.32),skin thickening(2.59±0.25),and scaling(2.52±0.29)compared to the methotrexate group,model control group,and blank control group(P<0.05).Additionally,the methotrexate group demonstrated reduced scores for erythema,skin thickening,and scaling compared to the model control group(P<0.05).(2)Hematoxylin-eosin(HE)staining revealed that the epidermis in the methotrexate group became thin-ner,with fewer parakeratotic cells and increased hair follicles.Conversely,the imiquimod group displayed abnor-mal cell morphology and relatively thicker white skin after modeling.(3)The imiquimod group showed significantly lower levels of TNF-α(51.63±4.39 pg/mL),IL-1β(35.53±4.15 pg/mL),IFN-γ(23.43±3.41 pg/mL),and IL-23(15.24±2.95 pg/mL)compared to the methotrexate and model control groups(P<0.05).Similarly,the methotrexate group exhibited reduced levels of TNF-α,IL-1β,IFN-γ,and IL-23 compared to the model control group(P<0.05).(4)The imiquimod group had significantly lower levels of CD8+CD103+cells(15.39±2.31)than the methotrexate and model control groups(P<0.05).Furthermore,the methotrexate group demonstrated lower levels of CD8+CD103+cells compared to the model control group(P<0.05).Conclusion Miquimod induces heavier skin lesions,faster response,and more epidermal thickening in psoriasis like mice.CD8+CD103+TRM cells and inflammatory factors may be involved in the recurrence of psoriasis.

Objective To observe the clinical efficacy of Lingnan fire needling in the treatment of plaque psoriasis.Methods A total of 60 cases of patients with plaque psoriasis admitted to Bao'an Hospital of Chinese Medicine Affiliated to Guangzhou University of Chinese Medicine from August 2021 to January 2023 were selected,and the patients were randomly divided into the observation group and the control group according to the random number table method,with 30 cases in each group.The observation group was given Lingnan fire needling for treatment,and the control group was given topical application of Calcipotriol Ointment.The course of treatment covered eight weeks continuously.After eight weeks of treatment,the clinical efficacy of the two groups was evaluated,and the changes of Psoriasis Area and Severity Index(PASI)scores and Dermatology Life Quality Index(DLQI)scores,as well as the diameter of glomus under dermoscopy of the patients in the two groups were observed before the treatment and after 2,4,6,and 8 weeks of treatment.Changes in Generalized Anxiety Disorder Scale(GAD-7)scores before treatment and after 2,4,6,and 8 weeks of treatment were compared between the two groups.Results(1)After 2,4,6 and 8 weeks of treatment,the scores of PASI,DLQI and GAD-7 of patients in the two groups were improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(2)The cured and markedly rate of the observation group was 86.67%(26/30);and that of the control group was 66.67%(20/30).The efficacy of the observation group was superior to that of the control group,the difference being statistically significant(P<0.05).(3)After 2,4,6,and 8 weeks of treatment,the diameter of glomus under dermoscopy of the patients in the two groups were improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).Conclusion Lingnan fire needling therapy for plaque psoriasis can effectively improve the clinical symptoms of the patients,relieve the anxiety symptoms induced by skin lesions and itching,so as to improve their quality of life.

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.