BACKGROUND:Spondylolisthesis is a common disease,and there is a lack of effective drugs to treat it.There is still a need to further define the pathogenesis and screen out more suitable therapeutic targets for spondylolisthesis.Mendelian randomization analysis can be used to explore the drugable genes associated with spondylolisthesis and provide valuable guidance for the development of more effective and targeted therapeutic drugs.OBJECTIVE:To explore potential therapeutic targets and effective drugs for spondylolisthesis by means of pharmaceutically available genome-wide Mendelian randomization analysis.METHODS:Using the Finnish database,eQTLGen consortium,drug signature database,drug-gene interaction database,protein-protein interaction database,organic small molecule biological activity database and protein structure database,which contains genome and health information of half a million Finns,data on druggable genes were subjected to two-sample Mendelian randomization analysis and co-localization analysis with data from genome-wide association studies of spondylolisthesis to identify genes highly associated with spondylolisthesis.In addition,GO and KEGG enrichment analysis,protein network construction,drug prediction and molecular docking were performed to provide valuable guidance for the development of more effective and targeted therapeutic agents.RESULTS AND CONCLUSION:In this study,we identified 34 potential drug target genes that were significantly associated with spondylolisthesis,particularly the gene APOBEC3G.This gene showed a significant association with spondylolisthesis outcomes through Mendelian analysis and co-localization analysis,suggesting that APOBEC3G may be a priority therapeutic target.As for other potential mechanisms and drugs,we still need to conduct more in-depth research to determine their roles.This study used a database from a European population,which can be used as a reference for the study of population genetics in China.

BACKGROUND:Spondylolisthesis is a common disease,and there is a lack of effective drugs to treat it.There is still a need to further define the pathogenesis and screen out more suitable therapeutic targets for spondylolisthesis.Mendelian randomization analysis can be used to explore the drugable genes associated with spondylolisthesis and provide valuable guidance for the development of more effective and targeted therapeutic drugs.OBJECTIVE:To explore potential therapeutic targets and effective drugs for spondylolisthesis by means of pharmaceutically available genome-wide Mendelian randomization analysis.METHODS:Using the Finnish database,eQTLGen consortium,drug signature database,drug-gene interaction database,protein-protein interaction database,organic small molecule biological activity database and protein structure database,which contains genome and health information of half a million Finns,data on druggable genes were subjected to two-sample Mendelian randomization analysis and co-localization analysis with data from genome-wide association studies of spondylolisthesis to identify genes highly associated with spondylolisthesis.In addition,GO and KEGG enrichment analysis,protein network construction,drug prediction and molecular docking were performed to provide valuable guidance for the development of more effective and targeted therapeutic agents.RESULTS AND CONCLUSION:In this study,we identified 34 potential drug target genes that were significantly associated with spondylolisthesis,particularly the gene APOBEC3G.This gene showed a significant association with spondylolisthesis outcomes through Mendelian analysis and co-localization analysis,suggesting that APOBEC3G may be a priority therapeutic target.As for other potential mechanisms and drugs,we still need to conduct more in-depth research to determine their roles.This study used a database from a European population,which can be used as a reference for the study of population genetics in China.

Dental caries,a chronic disease characterized by tooth decay,occupies the second position in terms of disease burden and is primarily caused by cariogenic bacteria,especially Streptococcus mutans,because of its acidogenic,aciduric,and biofilm-forming capabilities.Developing novel targeted anti-virulence agents is always a focal point in caries control to overcome the limitations of conventional anti-virulence agents.The current study represents an up-to-date review of in silico approaches of drug design against dental caries,which have emerged more and more powerful complementary to biochemical attempts.Firstly,we categorize the in silico approaches into computer-aided drug design(CADD)and AI-assisted drug design(AIDD)and highlight the specific methods and models they contain respectively.Subsequently,we detail the design of anti-virulence drugs targeting single or multiple cariogenic virulence targets of S.mutans,such as glucosyltransferases(Gtfs),antigen Ⅰ/Ⅱ(AgⅠ/Ⅱ),sortase A(SrtA),the VicRK signal transduction system and superoxide dismutases(SODs).Finally,we outline the current opportunities and challenges encountered in this field to aid future endeavors and applications of CADD and AIDD in anti-virulence drug design.

Objective To observe the efficacy of self-guided attention network for detecting responsible lesions related to cerebral palsy(CP)in children with periventricular white matter injury(PVWMI).Methods Totally 383 children with PVWMI were retrospectively enrolled and divided into CP group(n=243)and non-CP group(n=140),while 214 children without obvious brain abnormality on brain MRI were taken as control group.ROI of 4 key anatomical structures related to CP,i.e.centrum semiovale,posterior limb of internal capsule,cerebral peduncle and thalamus were delineated on T1WI,while responsible lesions related to CP within the key anatomical structures were labeled on T2WI,and the images were then registrated and used as input of the networks.ResNet34 network was adopted combined with attention and self-guided networks to train the network for detecting responsible lesions related to CP in children with PVWMI,and their efficacies were evaluated.The optimal network was screened,and its efficacy for segmenting the key anatomical structures was evaluated.Results Self-guided attention network was the optimal network,its area under the curve(AUC)for detecting lesions was 0.794-0.914,and the Dice similarity coefficient for segmenting the key anatomical structures was 0.702-0.764.Conclusion Self-guided attention network could be used for preliminarily detecting responsible lesions related to CP in children with PVWMI.

Objective To investigate the correlation between the anterior ethmoidal artery(AEA)and anatomical variations of the anterior cranial base,and to analyze the predictive factors for AEA suspension.Methods Sinus CT imaging data of 159 patients undergoing endoscopic sinus sur-gery(ESS)were retrospectively analyzed.Mimics 21.0 software was utilized for three-dimensional reconstruction,measuring parameters of AEA and anterior cranial base anatomy and performing classi-fication.Pearson and Spearman correlation analyses were used to evaluate the correlations among vari-ous anatomical parameters and their classifications.Multivariate binary logistic regression analysis was performed to screen for independentpredictive factors of AEA suspension.Results The rates of AEA suspension differed significantly across different Keros classifications(P＜0.001),with an increase rate as the Keros classification level increased(P＜0.001).The transverse diameter,height and vol-ume of supraorbital ethmoid cells(SOEC),olfactory fossa depth,lateral lamella of the cribriform plate(LLCP)length and frontal sinus pneumatization classification grade were positively correlated with the distance from AEA to the cranial base(P＜0.05).Multivariate binary Logistic regression analysis showed that the presence of SOEC(OR=4.178,95％CI,2.517 to 6.935,P＜0.001),in-creased olfactory fossa depth(OR=1.433,95％CI,1.197 to 1.715,P＜0.001),and higher frontal sinus pneumatization classification grade(OR=1.621,95％CI,1.121 to 2.345,P=0.01)were independent predictive factors for AEA suspension.Conclusion Detailed preoperative CT imaging assessment,especially the analysis of SOEC,olfactory fossa depth and frontal sinus pneumatization classification,aids in accurately assessing the anatomical position of AEA,thereby effectively reduc-ing the risk of AEA injury,and improving the safety and success rate of surgery.

Background and Purpose:Previous studies have investigated the prognostic significance of skeletal muscle and adipose tissue composition and distribution in colorectal cancer patients,yet most have not differentiated between rectal and colon cancer patient cohorts.This study aimed to explore the relationship between body composition and long-term prognosis,and to develop a postoperative predictive model.Methods:Clinical data of rectal cancer patients who underwent surgical treatment at Qingdao University Affiliated Hospital from January 2018 to December 2021 were retrospectively collected.Inclusion criteria:①Age＞18 years;② Preoperative colonoscopy and pathological diagnosis of colorectal cancer;③ Complete surgical resection;④Abdominal computed tomography(CT)scan 1 month before surgery.Exclusion criteria:① Clinical data is missing;② Multiple metastases of tumors;③ Tumor T stage 0 or carcinoma in situ;④ Severe artifacts lead to poor quality CT imaging,making it difficult to distinguish between fat and muscle;⑤ Inability to obtain follow-up results.This study has been approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University(approval number:QYFYWZLL30313),and informed consent has been waived in the ethical approval process.The skeletal muscle index(SMI)and subcutaneous adipose tissue index(SATI)were calculated by dividing the areas of skeletal muscle and subcutaneous fat observed on CT scans by the square of the patient's height.Univariate and multivariate COX regression analyses were conducted to identify risk factors influencing recurrence-free survival(RFS)and overall survival(OS)in rectal cancer patients.Based on the results of the multivariate analysis,a nomogram prediction model was developed,its predictive power and accuracy were assessed using the receiver operating characteristic(ROC)curve,calibration plots and decision curve analysis(DCA),and internal validation was conducted.Results:A total of 696 patients were included in this study,with 96(13.8%)patients experiencing postoperative recurrence and 89(12.8%)patients dying.Multivariate COX regression analysis showed that SMI,SATI,tumor T stage and N stage were independent factors affecting the postoperative RFS and OS of patients.Nomogram prediction models for RFS and OS in rectal cancer patients were constructed based on the above independent predictors.The area under ROC curve(AUC)for 3-,4-and 5-year RFS was 0.862,0.846 and 0.824,respectively;the AUC for 3-,4-and 5-year OS was 0.886,0.898 and 0.875,respectively.The models were evaluated using calibration curves and decision curves,and internal validation was performed,which showed that the prediction accuracy of the models was good.Conclusion:CT body composition is an independent predictor of RFS and OS in rectal cancer patients,and the nomogram model developed based on these factors demonstrates good predictive value for patient prognosis.

Objective To observe the efficacy of self-guided attention network for detecting responsible lesions related to cerebral palsy(CP)in children with periventricular white matter injury(PVWMI).Methods Totally 383 children with PVWMI were retrospectively enrolled and divided into CP group(n=243)and non-CP group(n=140),while 214 children without obvious brain abnormality on brain MRI were taken as control group.ROI of 4 key anatomical structures related to CP,i.e.centrum semiovale,posterior limb of internal capsule,cerebral peduncle and thalamus were delineated on T1WI,while responsible lesions related to CP within the key anatomical structures were labeled on T2WI,and the images were then registrated and used as input of the networks.ResNet34 network was adopted combined with attention and self-guided networks to train the network for detecting responsible lesions related to CP in children with PVWMI,and their efficacies were evaluated.The optimal network was screened,and its efficacy for segmenting the key anatomical structures was evaluated.Results Self-guided attention network was the optimal network,its area under the curve(AUC)for detecting lesions was 0.794-0.914,and the Dice similarity coefficient for segmenting the key anatomical structures was 0.702-0.764.Conclusion Self-guided attention network could be used for preliminarily detecting responsible lesions related to CP in children with PVWMI.

Malignant tumor is a serious and difficult disease threatening human health， which has a high morbidity and mortality rate worldwide. Traditional Chinese medicine has unique advantages in improving the therapeutic effect of malignant tumors and alleviating adverse reactions. Traditional Chinese medicine believes that Qi deficiency and blood stasis are important pathogeneses in the development of malignant tumors， and the method of supplementing Qi and activating blood is an effective strategy for treating malignant tumors. Astragali Radix， sweet in taste and warm in nature， has effects of tonifying Qi and rising Yang， strengthening the exterior and reducing sweat， promoting fluid and nourishing blood. Curcumae Rhizoma， acrid and bitter in taste and warm in nature， has the effects of promoting Qi and breaking blood stasis， eliminating mass， and relieving pain. Astragali Radix-Curcumae Rhizoma， as the classic herb pair of invigorating Qi and activating blood， has a clear effect on inhibiting tumor growth and metastasis. Studies have shown that Astragali Radix-Curcumae Rhizoma contains astragalus polysaccharide， astragaloside， calycosin， formononetin， curcumin， β-elemene， curcumenol， curcumenone， curcumendione， gemacrone， and other anti-tumor active ingredients. It can significantly inhibit the occurrence and development of liver cancer， colorectal cancer， gastric cancer， lung cancer， ovarian cancer， cervical cancer， breast cancer， and other cancers and has the advantages of superposition effect， synergistic complementarity， and increased dissolution compared with single herb and monomer of Chinese traditional herbs and has been widely valued in the field of TCM anti-cancer. Its anti-tumor mechanism includes inhibition of tumor cell proliferation， promotion of tumor cell apoptosis and autophagy， anti-invasion and metastasis， regulation of immune function， and enhancement of anti-tumor drug sensitivity. By combining Chinese and foreign literature， the compatibility effect and anti-tumor mechanism of Astragali Radix-Curcumae Rhizoma were summarized， and then scientific compatibility of these two herbs was expounded， in order to provide a useful reference for clinical application and future research of Astragali Radix-Curcumae Rhizoma.

Chemotherapy is an important treatment for tumors， but most patients experience varying degrees of chemotherapy- induced myelosuppression. Four properties theory of traditional Chinese medicine （TCM） has unique advantages in improving chemotherapy-induced myelosuppression. The monomers from TCM with different properties and flavors， such as cold-natured （e.g. Scutellaria baicalensis， Rhus chinensis）， cool-natured （e.g. Ligustrum lucidum， Ophiopogon japonicus）， warm-natured （e.g. Panax ginseng， Epimedium brevicornu， Curcuma longa， Angelica sinensis）， hot-natured （e.g. Cinnamomum cassia， Aconitum carmichaeli）， and neutral-natured （e. g. donkey-hide gelatin， Lycium barbarum， Rhodiola rosea， fungi）， can exert anti- myelosuppressive effects by reducing damage to hematopoietic stem/progenitor cells， improving the bone marrow hematopoietic microenvironment， inhibiting the oxidative stress response， regulating signaling pathways， so as to ultimately repaire inflammatory damage and improve hematopoietic function， thereby playing an anti-myelosuppressive role.