Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Under the background of carbon peaking and carbon neutrality goals, the Ministry of Ecology and Environment, together with 15 national ministries and commissions, has formulated the Implementation Plan on Establishing a Carbon Footprint Management System, and it is urgent for traditional Chinese medicine(TCM) pharmaceutical enterprises to carry out research on carbon footprint accounting methods of related products. Based on the life cycle assessment(LCA) theory, taking mulberry leaf extract produced by a certain enterprise as an example, this study analyzed the carbon footprint of TCM extracts during the life cycle. The results show that for every 1 kg of product produced, the carbon emissions from the stages of raw material acquisition, transportation, and extract production are-20.569, 1.205, and 173.577 kgCO_2eq(CO_2 equivalent), respectively. The carbon footprint of the product is 154.213 kgCO_2eq·kg~(-1). In addition, the carbon emission is the highest in the production stage, in which the consumption of ethanol solvents makes the greatest contribution to the carbon footprint, accounting for 25.71%, more than one-fourth of the total carbon footprint. The second contribution was from the treatment process of TCM residues, accounting for 19.67%, closely followed by wastewater treatment(17.71%), the consumption of hot steam(17.43%), and drinking water(16.90%). The consumption of electric power and packaging materials has a smaller carbon emission of 2.58%. In particular, the carbon emission caused by the consumption of packaging materials is only 0.04%, which is negligible. The results of the study are expected to provide a reference for TCM enterprises to carry out research on the carbon footprint of products, offer ideas for collaborative innovation in reducing pollution and carbon emissions throughout the entire industry chain of TCM, and develop new quality productivity of modern TCM industry based on green and low-carbon manufacturing.
Morus/chemistry* ; Plant Leaves/chemistry* ; Carbon Footprint ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts/analysis* ; Medicine, Chinese Traditional

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

OBJECTIVES: To investigate the molecular epidemiology of children with phenylketonuria (PKU) in Gansu, China, providing foundational data for intervention strategies. METHODS: A retrospective analysis was conducted on 1 159 PKU families who attended Gansu Provincial Maternity and Child Care Hospital from January 2012 to December 2024. Sanger sequencing, multiplex ligation-dependent probe amplification, whole exome sequencing, and deep intronic variant analysis were used to analyze the PAH gene. RESULTS: For the 1 159 children with PKU, 2 295 variants were identified in 2 318 alleles, resulting in a detection rate of 99.01%. The detection rates were 100% (914/914) in 457 classic PKU families, 99.45% (907/912) in 456 mild PKU families, and 96.34% (474/492) in 246 mild hyperphenylalaninemia families. The 2 295 variants detected comprised 208 distinct mutation types, among which c.728G>A (14.95%, 343/2 295) had the highest frequency, followed by c.611A>G (4.88%, 112/2 295) and c.721C>T (4.79%, 110/2 295). The cumulative frequency of the top 23 hotspot variants reached 70.28% (1 613/2 295), and most variant alleles were detected in exon 7 (29.19%, 670/2 295). CONCLUSIONS Deep intronic variant analysis of the PAH gene can improve the genetic diagnostic rate of PKU. The development of targeted detection kits for PAH hotspot variants may enable precision screening programs and enhance preventive strategies for PKU.
Humans ; Phenylketonurias/epidemiology* ; Female ; Male ; Retrospective Studies ; Phenylalanine Hydroxylase/genetics* ; Mutation ; Child, Preschool ; China/epidemiology* ; Child ; Infant

Diabetic kidney disease (DKD) with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression. Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials. In this study, we integrated large-scale plasma proteomics, genetic-driven causal inference, and experimental validation to identify prioritized targets for DKD using the UK Biobank (UKB) and FinnGen cohorts. Among 2844 diabetic patients (528 with DKD), we identified 37 targets significantly associated with incident DKD, supported by both observational and causal evidence. Of these, 22% (8/37) of the potential targets are currently under investigation for DKD or other diseases. Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4 (IGFBP4), family with sequence similarity 3 member C (FAM3C), and prostaglandin D2 synthase (PTGDS)-were associated with a 4.35, 3.51, and 3.57-fold increased likelihood of developing DKD, respectively. In addition, population-level protein-altering variants (PAVs) analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD, through the classic NLR family pyrin domain containing 3 (NLRP3)-caspase-1-gasdermin D (GSDMD) apoptotic axis. Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

Objective To evaluate the efficacy and safety of systemic thrombolysis(ST)and standard anticoagulation(SA)in the treatment of lower extremity fracture complicated with distal deep vein thrombosis(DDVT).Methods We retrospectively analyzed the clinical data of 60 patients with lower extremity fracture complicated with DDVT treated from January 2021 to December 2023.When the lower limb venography indicated a calf thrombus burden score ≥3 points,a retrievable inferior vena cava filter(IVCF)was successfully placed in the healthy femoral vein before orthopedic surgery.The patients who received further anticoagulant or thrombolytic therapy after surgery were allocated into a ST group(n=30,urokinase ST and SA)and a SA group(n=30,only SA).The two groups were compared in terms of calf thrombus burden score,thrombus dissolution rate,IVCF placement time,IVCF retrieval rate,intercepted thrombi,hemoglobin level,platelet count,D-dimer level,and complications.Results There was no statistically significant difference in the calf thrombus burden score between the two groups before treatment(P=0.431).However,after treatment,the scores in both groups decreased(both P<0.001),with the ST group showing lower score than the SA group(P=0.002).The thrombus dissolution rate in the ST group was higher than that in the SA group(P<0.001).There was no statistically significant difference in the IVCF placement time between the two groups(P=0.359),and the IVCF retrieval rate was 100% in both groups.The ST group had fewer intercepted thrombi than the SA group(P=0.002).There was no statistically significant difference in hemoglobin level(P=0.238),platelet count(P=0.914),or D-dimer level(P=0.756)between the two groups before treatment.However,after treatment,both groups showed an increase in platelet count(both P<0.001)and a decrease in D-dimer level(both P<0.001).There was no statistically significant difference in the occurrence of complications between the two groups(P=0.704).Conclusions Both SA and ST demonstrate safety and efficacy in the treatment of lower extremity fractures complicated with DDVT,serving as valuable options for clinical application.Compared with SA,ST not only enhances the thrombus dissolution in the calf but also mitigates the risk of thrombosis associated with IVCF.
Humans ; Venous Thrombosis/therapy* ; Retrospective Studies ; Thrombolytic Therapy/methods* ; Male ; Female ; Middle Aged ; Fractures, Bone/complications* ; Lower Extremity/injuries* ; Anticoagulants/therapeutic use* ; Aged ; Treatment Outcome ; Adult

Objective To explore the relationship between levels of vascular endothelial growth factor(VEGF),insulin-like growth factor 1(IGF-1),and transforming growth factor-β1(TGF-β1)in the synovial fluid of children with avascular necrosis of the femoral head(also known as Perthes disease)and the efficacy of postoperative revascularization,aiming to provide a basis for subsequent diagnosis and treatment.Methods A retrospective study was conducted on 262 children with Perthes disease admitted to the Affiliated Hospital of Gansu University of Chinese Medicine from January 2023 to June 2024.Based on postoperative revascularization efficacy,patients were divided into good revascularization group(n=228)and poor revascularization group(n=34).For poor revascularization group,a 1:2 matched case-control design was used to select 68 age-matched children with hip synovitis who underwent hip joint fluid puncture as control group.Additionally,82 children with Perthes disease treated at the hospital from June 2024 to January 2025 were enrolled as a validation cohort for nomogram model verification.The expression levels of VEGF,IGF-1 and TGF-β1 in the synovial fluid of three groups were compared.Confounding biases were controlled through univariate and stratified analyses.Binary logistic regression analysis was used to identify independent factors affecting the revascularization effect.R software was utilized to draw and verify the nomogram model for predicting the postoperative revascularization effect.Results The levels of VEGF,IGF-1 and TGF-β1 in the synovial fluid of children in poor revascularization group were all higher than those in control group and good revascularization group(P<0.05).After three types of reconstructive surgeries,the levels of VEGF,IGF-1 and TGF-β1 in the synovial fluid of children with poor revascularization were all higher than those in children with good revascularization(P<0.05);however,there was no statistically significant difference in the above indicators among different surgical types(P>0.05).Binary logistic regression analysis showed that the levels of VEGF,IGF-1,and TGF-β1 in the synovial fluid were independent risk factors for poor postoperative revascularization in children with Perthes disease.The area under the ROC curve of the nomogram model established accordingly for predicting poor postoperative revascularization in children with Perthes disease was 0.875(95%CI 0.805-0.945),with a sensitivity of 0.874 and a specificity of 0.851.Moreover,the calibration curve and decision curve analysis(DCA)indicated that the model had good clinical applicability.Conclusions The increased levels of VEGF,IGF-1 and TGF-β1 in synovial fluid are associated with poor postoperative revascularization in children with Perthes disease.These three factors are expected to become prognostic indicators for children with Perthes disease.

Diabetic kidney disease(DKD)with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression.Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials.In this study,we integrated large-scale plasma proteomics,genetic-driven causal inference,and experimental validation to identify prioritized targets for DKD using the UK Biobank(UKB)and FinnGen cohorts.Among 2844 diabetic patients(528 with DKD),we identified 37 targets significantly associated with incident DKD,supported by both observational and causal evi-dence.Of these,22％(8/37)of the potential targets are currently under investigation for DKD or other diseases.Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4(IGFBP4),family with sequence similarity 3 member C(FAM3C),and prostaglandin D2 synthase(PTGDS)—were associated with a 4.35,3.51,and 3.57-fold increased likeli-hood of developing DKD,respectively.In addition,population-level protein-altering variants(PAVs)analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD,through the classic NLR family pyrin domain containing 3(NLRP3)-caspase-1-gasdermin D(GSDMD)apoptotic axis.Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.