Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective·To investigate the clinicopathologic features,gene mutation profile,and real-world survival prognosis of diffuse large B-cell lymphoma(DLBCL)with pulmonary involvement.Methods·The clinical data of 110 patients with newly diagnosed,pathologically confirmed DLBCL and pulmonary involvement at Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,between August 2003 and December 2022 were retrospectively collected and analyzed.Evaluation of the efficacy of treatment,survival analyses,and univariate and multivariate analyses were performed in 88 patients who received a first-line regimen based on rituximab in combination with cyclophosphamide,doxorubicin/epirubicine,vincristine,and prednisone(R-CHOP).A total of 74 patients underwent targeted DNA sequencing of 55 lymphoma-related genes and were evaluated for mutations.Results·Among the 110 patients,72(65.5%)were>60 years old,52(47.3%)were female,92(83.6%)presented with Ann Arbor stage Ⅲ?Ⅳ,20(18.2%)had ECOG scores≥2,75(68.2%)had elevated lactate dehydrogenase(LDH)levels,79(71.8%)had≥2 extranodal involvements,32(31.4%)were classified as germinal center B-cell subtype,22(26.8%)were diagnosed with double expressor lymphoma,and 4(4.6%)with double-hit lymphoma.Among the patients treated with R-CHOP-based first-line regimens,the objective response rate(ORR)was 68.2%,the 5-year progression-free survival(PFS)rate was 43.7%,and the 5-year overall survival(OS)rate was 65.4%.Univariate analysis showed that elevated LDH and ECOG score≥2 were poor prognostic factors for PFS and OS,and mutations in PIM1 and CD79B were poor prognostic factors for PFS among high-frequency mutations.Multivariate analysis showed that elevated LDH was an independent adverse prognostic factor for PFS(HR=2.47,95%CI 1.28?4.77)and OS(HR=2.71,95%CI 1.21 ? 6.07).Targeted sequencing results showed that PIM1(25.7%),MYD88(24.3%),TP53(18.9%),CD79B(17.6%),KMT2D(17.6%),and TNFAIP3(16.2%)were the high-frequency mutations with mutation rates over 15%.Conclusion·Elevated LDH is an independent adverse prognostic factor for PFS and OS in DLBCL with pulmonary involvement.Mutations in PIM1,MYD88,TP53,CD79B,KMT2D,and TNFAIP3 are frequently observed in this population.

Objective Systematic identification and analysis of the cytochrome P450(CYP450)gene family members and their functions in Chrysanthemum indicum L.to provide a basis for further studies on their roles in the flavonoid synthesis pathway.Methods Based on the genomic data of a diploid Chrysanthemum indicum L.,the members of the P450 gene family were identified and analyzed using bioinformatics methods.Moreover,the transcriptome and quasi-targeted metabolome analysis were combined to screen the flavone synthase Ⅱ(FNSII)genes from the CYP93 family,and their expression levels were tested in different tissues of C.indicum using real-time fluorescence quantitative PCR(qPCR).Results A total of 460 P450 genes were identified from the C.indicum genome,belonging to 43 families within 8 family clans.The encoded proteins ranged from 336 to 1538 amino acids in length,with a relative molecular mass between 38.01 to 175.00 kDa,and an isoelectric point between 5.61 to 9.71.Chromosome localization analysis indicated that these 460 P450 genes were unevenly distributed on nine chromosomes,with the highest number of light-responsive elements in the promoter regions.Expression pattern analysis showed that the expression levels of two FNSII genes(CindChr2G00102820.1 and CindChr8G00552890.1)were significantly higher in leaf of C.indicum than in flower.Conclusion The comprehensive analysis of the P450 gene family in C.indicum is helpful to further elucidate the function of the P450 gene family in flavonoid biosynthesis.

Objective To investigate the value of machine learning models based on contrast-enhanced CT radiomics in differentia-ting renal oncocytoma(RO)from chromophobe renal cell carcinoma(chRCC).Methods A total of 65 patients with RO and chRCC confirmed by pathology with complete clinical and imaging data were analyzed retrospectively.The patients were randomly divided into training set(n=45)and test set(n=20)according to a ratio of 7︰3.The tumor boundaries were delineated on the preoperative CT images using 3D Slicer software,and radiomics features were extracted using the Radiomics plugin.Univariate analysis,recursive fea-ture elimination(RFE),least absolute shrinkage and selection operator(LASSO)algorithms were used to select the best radiomics features.Three machine learning models were constructed on the training set and the grid search method was used to select the best combination of hyperparameters.The receiver operating characteristic(ROC)curve,calibration curve and decision curve were used to evaluate the performance of each machine learning model on the training set and test set.Results Random forest model,logistic regres-sion model and support vector machine model can better identify RO and chRCC.In the training set,the area under the curve(AUC)of random forest model and support vector machine model were 0.950[95%confidence interval(CI)0.901-0.998]and 0.955(95%CI 0.908-1.000),respectively,which were higher than the AUC of logistic regression model 0.882(95%CI 0.806-0.956).Statistical differences were found by DeLong test(P<0.05);In the test set,the AUC of random forest model,logistic regression model and support vector machine model were 0.876(95%CI 0.758-0.993),0.883(95%CI 0.768-0.997)and 0.883(95%CI 0.768-0.997),respectively.There was no significant statistical difference in the AUC of each model by DeLong test(P>0.05).The decision curve showed that all three models had significant net clinical benefits.Conclusion The machine learning model based on contrast-enhanced CT radiomics can effectively distinguish RO from chRCC.

Objective To investigate the value of machine learning models based on contrast-enhanced CT radiomics in differentia-ting renal oncocytoma(RO)from chromophobe renal cell carcinoma(chRCC).Methods A total of 65 patients with RO and chRCC confirmed by pathology with complete clinical and imaging data were analyzed retrospectively.The patients were randomly divided into training set(n=45)and test set(n=20)according to a ratio of 7︰3.The tumor boundaries were delineated on the preoperative CT images using 3D Slicer software,and radiomics features were extracted using the Radiomics plugin.Univariate analysis,recursive fea-ture elimination(RFE),least absolute shrinkage and selection operator(LASSO)algorithms were used to select the best radiomics features.Three machine learning models were constructed on the training set and the grid search method was used to select the best combination of hyperparameters.The receiver operating characteristic(ROC)curve,calibration curve and decision curve were used to evaluate the performance of each machine learning model on the training set and test set.Results Random forest model,logistic regres-sion model and support vector machine model can better identify RO and chRCC.In the training set,the area under the curve(AUC)of random forest model and support vector machine model were 0.950[95%confidence interval(CI)0.901-0.998]and 0.955(95%CI 0.908-1.000),respectively,which were higher than the AUC of logistic regression model 0.882(95%CI 0.806-0.956).Statistical differences were found by DeLong test(P<0.05);In the test set,the AUC of random forest model,logistic regression model and support vector machine model were 0.876(95%CI 0.758-0.993),0.883(95%CI 0.768-0.997)and 0.883(95%CI 0.768-0.997),respectively.There was no significant statistical difference in the AUC of each model by DeLong test(P>0.05).The decision curve showed that all three models had significant net clinical benefits.Conclusion The machine learning model based on contrast-enhanced CT radiomics can effectively distinguish RO from chRCC.

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Background: Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials. Microbial agents, as environmentally friendly and efficient plant growth promoters and soil conditioners, have increasingly attracted attention in eco-agriculture research. Objective: Our understanding remains limited regarding how the application of microbial agents, alone or in combination, affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials. Methods: In this study, Epimedium pubescens Maxim. was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis) applied individually and in combination on plant growth and the accumulation of bioactive components. Additionally, this study explored the relationship between the rhizosphere microbiome and plant development. Results: The application of microbial agents increased the yield of E. pubescens leaves by 20.30% to 33.66% and enhanced the total flavonol glycosides content by 11.40% to 29.94%. Meanwhile, microbial treatments reshaped the rhizosphere microbiome, promoted the enrichment of beneficial microorganisms (e.g., Frankia and Paenibacillus), suppressed phytopathogenic fungi such as Didymella and Scytalidium, and enhanced the stability of the soil microbial co-occurrence network. The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumulation of bioactive components by modulating the soil microbiome. Conclusion: These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere microbiomes as mediated by microbial agents. They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Objective:To investigate the applicability and surgical effect of direct horizontal suture in the repair of defects after the excision of eyelid nevus.Methods:The clinical data of patients with eyelid nevus who were admitted to Department of Facial and Neck Plastic Surgery, Plastic Surgery Hospital of Chinese Academy of Medical Sciences from March 2015 to March 2023 were retrospectively analyzed. After the eyelid nevus was removed, the defect was closed by horizontal suture parallel to the eyelid margin. In the preoperative simulation suture scheme, one or more horizontal lines were marked on the eyelid skin according to the scope of the nevus. The intersection points of the horizontal lines and the edges of the nevus were marked for simulated suturing. If the marked points aligned horizontally, direct suturing was applied. After 3 months of postoperative follow-up, the therapeutic effect was evaluated based on eyelid function (classified as excellent, good and poor), cosmetic effects (classified as excellent, good and poor) and patient satisfaction (classified as very satisfactory, satisfactory and dissatisfactory). At the same time, the effect of different wound length (<1 cm, 1-2 cm, >2 cm) on the therapeutic effect was also analyzed. SPSS 27.0 software was used for statistical analysis of the data. The counting data were represented by examples and percentages, and Kruskal-Wallis H test was used for comparison between groups. P<0.05 indicated that the difference was statistically significant. Results:A total of 71 patients were enrolled, including 30 males and 41 females. Aged 4 to 35 years old, with an average age of 15 years old. The lesions involved the upper eyelid in 47 cases, the lower eyelid in 14 cases, and co-involved in 10 cases. Lesion areas ranged from 0.5 cm×0.5 cm to 2.3 cm×2.0 cm. None of the lesions involved the palpebral margin and conjunctiva, and the depth did not reach the orbicularis oculi muscle. Immediately after the operation, all the patients had different degrees of eyelid deformation, and some severe patients had difficulty opening their eyes. The above symptoms were relieved within 7 days to 3 months after the operation, and eventually the eyelid movement returned to normal, leaving only mild scarring. In cases where the eyelid nevus was close to or involved the eyebrow area, eyebrow shape changed after surgery, and it gradually returned to normal after 1 month. Some patients with part of the eyebrow defect were able to improve their appearance through eyebrow tattoos, eyebrow transplatation and other methods. The eyelid function of 71 patients was excellent. The evaluation of cosmetic effect, 41 cases (58%) were excellent, and 30 cases (42%) were good. The evaluation of patient satisfaction, 56 cases (79%) were very satisfied, and 15 cases (21%) were satisfied. Statistical analysis showed that with the increase of the horizontal length of the wound, the cosmetic effect and patient satisfaction would be affected to a certain extent, but the differences were not statistically significant ( P>0.05). Conclusion:For eyelid nevus excision defects that can be closed horizontally, direct suturing method should be considered priority. This method is simple to perform, offers stable postoperative effects, and leads to high patient satisfaction.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.