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.

This paper aimed to explore the effects of Duzhong Decoction(DZD)-containing serum on the proliferation and osteoblast differentiation of MC3T3-E1 cells through L-type voltage-gated calcium channels(L-VGCCs). L-VGCCs inhibitors, nifedipine and verapamil, were used to block L-VGCCs in osteoblasts. MC3T3-E1 cells were divided into a control group, a low-dose DZD-containing serum(L-DZD) group, a medium-dose DZD-containing serum(M-DZD) group, a high-dose DZD-containing serum(H-DZD) group, a nifedipine group, a H-DZD + nifedipine group, verapamil group, and a H-DZD + verapamil group. The CCK-8 method was used for cell proliferation analysis, alkaline phosphatase(ALP) assay kits for intracellular ALP activity measurement, Western blot for protein expression level in cells, real-time fluorescence quantitative PCR technology for intracellular mRNA expression level determination, fluorescence spectrophotometer for free Ca~(2+) concentration determination in osteoblasts, and alizarin red staining(ARS) for mineralized nodule formation in osteoblasts. The experimental results show that compared to the control group, DZD groups can promote MC3T3-E1 cell proliferation, ALP activity, and mineralized nodule formation, increase intracellular Ca~(2+) concentrations, and upregulate the protein expression of bone morphogenetic protein 2(BMP2), collagen Ⅰ(COL1), α2 subunit protein of L-VGCCs(L-VGCCα2), and the mRNA expression of Runt-related transcription factor 2(RUNX2), and BMP2. After blocking L-VGCCs with nifedipine and verapamil, the intervention effects of DZD-containing serum were inhibited to varying degrees. Both nifedipine and verapamil could inhibit ALP activity, reduce mineralized nodule areas, and downregulate the expression of bone formation-related proteins. Moreover, the effects of DZD-containing serum on increasing MC3T3-E1 cell proliferation, osteoblast differentiation, and Ca~(2+) concentrations, upregulating the mRNA expression of osteoprotegerin(OPG) and protein expression of phosphorylated protein kinase B(p-Akt) and phosphorylated forkhead box protein O1(p-FOXO1), and upregulating phosphatase and tensin homolog(PTEN) expression were reversed by nifedipine. The results indicate that DZD-containing serum can increase the Ca~(2+) concentration in MC3T3-E1 cells to promote bone formation, which may be mediated by L-VGCCs and the PTEN/Akt/FoxO1 signaling pathway, providing a new perspective on the mechanism of DZD in treating osteoporosis.
Animals ; Osteoblasts/metabolism* ; Cell Proliferation/drug effects* ; Cell Differentiation/drug effects* ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Calcium Channels, L-Type/genetics* ; Alkaline Phosphatase/genetics* ; Serum/chemistry* ; Cell Line ; Osteogenesis/drug effects* ; Bone Morphogenetic Protein 2/genetics*

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control

OpenSim is an open source, free motion simulation and gait analysis software, which can be used to dynamically simulate and analyze the complex motion of the human body, and is widely used in human biomechanical research. Since OpenSim can analyze multi-dimensional motion data such as muscle strength, joint torque, and muscle synergistic activation during human movement, it can be used to study the biomechanical mechanism of musculoskeletal imbalance diseases and various treatment methods in TCM orthopedics, and has a broad application prospect in the field of TCM orthopedics. By the analysis of the basic characteristics, elements, analysis process, and application prospects of OpenSim, it is concluded that OpenSim musculoskeletal model has a large application space in the field of traditional Chinese medicine orthopedic, which is helpful to explain the pathogenesis and mechanism of diseases, and promote the precision diagnosis and treatment of orthopedics diseases;the application of OpenSim musculoskeletal model can solve the problem that the previous research paid attention to the bone malalignment and not enough attention to the tendon, and provide a new method for the research of orthopedic diseases. At present, there are still problems in the promotion and application of OpenSim, such as large equipment requirements and high operation threshold. Therefore, multidisciplinary cooperation, clinical research, and data sharing are the basic research strategies in this field.
Humans ; Biomechanical Phenomena ; Orthopedics ; Traumatology ; Software ; Medicine, Chinese Traditional ; Musculoskeletal System ; Models, Biological

Objective To investigate the genetic differences among different populations based on 13 autosomal STR loci in CODIS core.Methods Data of 13 autosomal STR loci(CSF1PO,FGA,THO1,TPOX,vWA,D3S1358,D5S818,D7S820,D8S1179,D13S317,D16S539,D18S51,D21S11)were collected from 95 populations in scientific journals between 1999 and 2021,soursed from the PubMed database,which had been published.Allele frequencies of loci were sorted out and forensic genetic parameters including gene differentiation coefficient(Gst),total heterozygosity(Ht),subpopula-tion heterozygosity(Hs)values,and Nei's DA genetic distance were calculated.Principal component analysis,phylogenetic tree,and multidimensional scale analysis were conducted to assess population ge-netic structure.Results A total of 265 alleles were detected at the 13 STR loci in these 95 popula-tions.The mean values of Gst,Ht,and Hs were 0.023 247,0.797 915 and 0.779 365.Population genetic analyses reflected significant differences among populations from Asia,Africa and Europe.In Asian populations,there was a certain degree of distinction between mainland and island populations;the Han population showed a certain degree of distinction with surrounding populations in mainland;while within the Han population,there were two distinct clusters formed by the northern Han and the south-ern Han.Conclusion The 13 autosomal STR loci in CODIS core demonstrate potential value for popu-lation identification across different groups,and may be used for the differentiation of ethnic groups,among different continental populations.

Objectives:To investigate the physical growth status of pediatric patients with transfusion-dependent thalassemia (TDT) and analyze the effects of treatment-related and socioeconomic factors on physical growth.Methods:Based on the specialized thalassemia database from gene therapy clinical research at the Institute of Hematology & Hospital of Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, we collected data on height and weight development, family economic status, and medical records of 338 pediatric patients with TDT from October 2023 to May 2024. The length/height-for-age and body mass index (BMI) -for-age were classified based on the Growth Standard for Children under 7 Years of Age, Standard for Height Level Classification among Children and Adolescents Aged 7-18 Years, and Dietary Guidelines for Chinese Residents. Logistic regression analysis was conducted to assess the effects of family economic status and disease-related treatment on length/height-for-age and BMI-for-age.Results:Among the 338 patients, 118 were children and 220 were adolescents (192 males and 146 females), with a median age of 12 years (range: 0.8-18) and a median diagnosis duration of 10.3 years (range: 0.5-17.9). Subtypes included α-thalassemia [21 cases (6.2%) ], β-thalassemia [288 cases (85.2%) ], and combined αβ-thalassemia[29 cases (8.6%) ]. The monthly household income of patients was concentrated in 3 000-5 000 yuan (39.9%) and 5 001-10 000 yuan (34.9%), whereas 67.2% of the families had monthly medical expenses of <3 000 yuan. Of the patients, 75.5% received their first transfusion before 1 year of age. The proportions of children and adolescents with pretransfusion hemoglobin (HGB) of ≤70 g/L were 4.2% and 6.4%, respectively. Adolescents demonstrated significantly higher rates of transfusion frequency of <4 weeks/session, monthly red blood cell infusion of >2 U, serum ferritin (SF) of ≥5 000 μg/L, iron chelation therapy, and splenectomy compared with children (all P<0.05). Of the 338 patients, 26.0%, 22.8%, and 8.9% demonstrated stunted growth, underweight, and concurrent stunted growth with underweight, respectively. No significant difference was observed in the stunted growth rates between children (22.9%) and adolescents (27.7%) ( P=0.402). However, the underweight rate in adolescents (26.8%) was significantly higher than that in children (15.3%) ( P=0.023). The multivariate analysis determined the following risk factors for stunted growth: monthly household income of <10 000 yuan (5 001-10 000 yuan: OR=5.49, 95% CI: 1.48-35.76; 3 000-5 000 yuan: OR=6.87, 95% CI: 1.88-44.60; <3 000 yuan: OR=9.29, 95% CI: 2.20-64.77), pretransfusion HGB of ≤70 g/L ( OR=3.25, 95% CI: 1.07-10.18), and SF of ≥5 000 μg/L ( OR = 3.04, 95% CI: 1.20-7.70). Longer diagnostic duration was associated with underweight ( OR=1.10, 95% CI: 1.01-1.20) . Conclusions:Children and adolescents with TDT with pretransfusion SF of ≥5 000 μg/L, HGB of ≤70 g/L, low monthly household income, or longer diagnosis duration were significantly more likely to experience delayed physical growth.

Objective:To evaluate the efficacy of cyclophosphamide in patients with T-cell large granular lymphocytic leukemia (T-LGLL) and the maintenance of treatment-free remission (TFR) following drug discontinuation.Methods:Clinical data were collected from 37 patients with T-LGLL who received oral cyclophosphamide at the Regenerative Medicine Clinic of the Institute of Hematology and Blood Diseases Hospital between June 2019 and March 2024. Patient clinical characteristics, treatment efficacy, and long-term TFR were analyzed.Results:The median age of the 37 patients was 60 years (range: 37-86), and 22 (59.5%) were male. Anemia was observed in 30 patients (81.1%), and 28 (75.7%) met the diagnostic criteria for secondary pure red cell aplasia. Neutropenia occurred in 15 patients (40.5%), lymphocytosis in 11 (29.7%), and thrombocytopenia in three (8.1%). Sixteen patients (43.2%) had not received prior immunosuppressive therapy (treatment-naive group), while 21 patients (56.8%) were refractory to or had relapsed after immunosuppressive treatment (refractory/relapsed group). All patients met the treatment criteria and received oral cyclophosphamide at doses of 50-100 mg/day. Among the 36 evaluable patients, hematologic remission was achieved in 25 (69.4%), with a median time of 2.0 months (range: 0.7-7.0). There was no statistically significant difference in remission rates between the treatment-naive and refractory/relapsed groups (68.5% vs. 66.7%, P=0.589). Among the 25 patients who achieved hematologic remission, 24 discontinued cyclophosphamide. With a median follow-up of 39.0 months (range: 8.0-56.0), the median TFR duration was not reached. The estimated TFR rates were (90.87± 6.16) % at 12 months and (75.72±11.04) % at 36 months. No significant difference in TFR was observed between the treatment-naive and refractory/relapsed groups ( P=0.451) . Conclusion:Oral cyclophosphamide is effective in the treatment of T-LGLL, and patients may maintain long-term TFR following drug discontinuation.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Myxedema coma is a rare condition, typically arising from long-standing, untreated hypothyroidism and triggered by factors such as infection, hypothermia, or severe illness. This report details a successfully treated case of myxedema coma with cardiac attest, accompanied by a literature review, to enhance clinical awareness and improve the diagnosis and management of this critical condition.