The promulgation of the Technical Specifications for Clinical Use of Blood (2025 Edition) signifies that China's clinical blood transfusion management has transitioned from mere technical operations to a new stage centered on patient blood management (PBM). Through an in-depth comparison of the new and old specifications, this paper analyzes the core transformations regarding conceptual reconstruction, legal alignment, technological upgrades, and closed-loop management. The new specifications establish PBM principles, reinforce legal safeguards for informed consent and emergency treatment, and construct a comprehensive, refined quality control system by specifying compatibility testing standards and introducing a post-transfusion evaluation system. Medical institutions should seize this opportunity to update management protocols and information systems, deepen multidisciplinary collaboration, and drive the profound transformation of clinical blood use from focusing solely on safety assurance to placing equal emphasis on science and value.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Cancer stem cells (CSCs) represent a distinct subpopulation of cells characterized by self-renewal capacity, differentiation potential, and critical roles in driving tumor progression, therapeutic resistance, recurrence, and maintenance of the tumor microenvironment. Targeting CSCs has emerged as a pivotal direction in cancer research, offering novel strategies to overcome drug resistance and prevent metastasis and relapse. Lysosomes, traditionally recognized as central organelles for intracellular degradation and recycling, are indispensable for cellular homeostasis. Dysregulation of lysosomal function is intimately linked to various diseases, including cancer. In tumors, aberrant lysosomal activity can promote malignant progression through mechanisms such as altering metabolic pathways, enhancing lysosomal exocytosis, modulating drug resistance, and interfering with autophagy-lysosomal pathways. Recent studies have underscored the involvement of lysosomes in regulating CSC properties. This review synthesizes findings on lysosomal regulation of CSCs through the following aspects. (1) Lysosomes exert complex and critical bidirectional control over CSC stemness maintenance through three degradation pathways that are dependent on their degradative function. (i) The lysophagy pathway. This pathway exhibits dual roles. Activation can sustain CSC functions; for instance, in glioblastoma, hypoxia upregulates Gal-8 via the STAT3/HIF1α signaling axis to induce autophagy, supporting stem cell survival. In head and neck squamous cell carcinoma, degradation of GSK3β activates the Wnt pathway, enhancing stemness. Conversely, this pathway can suppress stemness by degrading stemness-related proteins such as BMI-1 and OCT4A, thereby impairing CSC self-renewal capacity. (ii) Mitophagy pathway. In non-small cell lung cancer stem cells, mitophagy-related mechanisms, such as the accumulation of mitochondrial DNA (mtDNA) activating the TLR9-Notch1-AMPK signaling axis, have been shown to promote CSC proliferation. (iii) Autophagosome-dependent lysosomal degradation pathway. This pathway directly regulates stemness-related proteins in a bidirectional manner. Enhanced degradative function can promote CSC properties, exemplified by the degradation of NUMB to activate Notch signaling. Conversely, attenuated degradative function can also enhance stemness by stabilizing oncoproteins (e.g., protecting Frizzled-1 from degradation to sustain Wnt signaling) or preventing the degradation of tumor suppressors (e.g., inhibiting Notch degradation). (2) Constituent proteins of lysosomes, including membrane proteins and luminal acid hydrolases, participate in regulating CSC stemness. Regarding membrane proteins, LAMP2A facilitates chaperone-mediated autophagy to maintain stemness in glioblastoma and ovarian cancer. V-ATPase, by maintaining an acidic luminal environment, promotes proliferation and drug resistance in glioma stem cells. Among hydrolases, cathepsins B and L are highly expressed in pancreatic and ovarian cancers and correlate with poor prognosis. Furthermore, targeting lysosomes to induce lysosomal membrane permeabilization (LMP) triggers lysosome-mediated cell death, presenting a potential therapeutic strategy for eradicating CSCs.(3) The acidic luminal environment, single-membrane structure, and the presence of transmembrane transporters (e.g., ABCA3) enable lysosomes to passively trap or actively uptake and sequester chemotherapeutic drugs. Subsequent drug extrusion via exocytosis confers drug resistance. In CSCs, this lysosome-mediated drug sequestration, often cooperating with autophagy, establishes multimodal drug resistance. Therefore, targeting lysosomal function represents a potential strategy to overcome therapy resistance. The central role of lysosomes in regulating CSC stemness and resistance positions them as highly promising therapeutic targets. Strategies aimed at disrupting lysosomal function to selectively eliminate CSCs include: inhibiting the lysosome-autophagy system using agents like IITZ or lovastatin; inducing lysosomal membrane permeabilization (LMP) with compounds such as hexamethylene amiloride to compromise membrane stability; and disrupting the acidic luminal environment using drugs like siramesine or the K/H transport compound 2. In conclusion, lysosomes critically regulate CSC stemness maintenance and drug resistance through degradative pathways, membrane protein functions, luminal hydrolase activities, and drug sequestration mechanisms. This redefines the lysosome from a traditional “waste disposal unit” to a “signal integration center” in CSCs. The duality and context-dependency of lysosomal function in CSCs offer novel insights into the heterogeneity observed across different tumors. Targeting lysosomal vulnerabilities—such as inducing LMP, disrupting acidity, or blocking autophagic flux—provides a strategy to bypass canonical CSC resistance mechanisms and directly trigger cell death. This establishes the lysosome as a key target to overcome CSC-mediated therapy resistance, paving the way for developing diverse candidate drugs and innovative combination therapies in oncology.

[Objective] To analyze the effects of different factors and red blood cell transfusion thresholds on the efficacy of neonatal red blood cell (RBC) transfusion, in order to provide more references for neonatal transfusions to better achieve rational and effective blood use. [Methods] A retrospective collection of data from 282 neonates who received RBC transfusions at our hospital from 2022 to 2023 was conducted, including birth weight, gestational age, number of blood transfusions, length of hospital stay, assisted ventilation during RBC transfusion, and laboratory test results before and after transfusion. SPSS software was used for statistical analysis to comprehensively analyze the impact of different factors on the efficacy of RBC transfusion in neonates. [Results] The results showed that the gestational age and weight of newborns at birth were negatively correlated with their length of hospital stay and the number of RBC transfusions during hospitalization. Newborns with younger gestational age and lower weight had longer hospital stays and more RBC transfusions during hospitalization. After administering RBCs according to the standard of 15 mL/kg, there was a statistically significant difference in the efficacy of RBC transfusion at different transfusion thresholds. In non-critical situations, RBC transfusions were ineffective when the pre-transfusion hemoglobin (Hb) level was >120 g/L. When the pre-transfusion Hb level was ≤70 g/L, RBC transfusions achieved higher efficacy in both critical and non-critical situations. [Conclusion] In critical situations, the group with pre-transfusion Hb values ≤ 70 g/L has the best RBC transfusion effect, while in non-critical situations, the group with pre-transfusion Hb levels between 81 and 90 g/L has the best RBC transfusion effect. Overall, the efficacy of RBC transfusion in non-critical situations is higher than that in critical situations.

Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective: To establish a machine learning-based precision blood donor recruitment model at the county level and assess its generalizability and applicability. Methods: A retrospective study was conducted using blood donation and SMS recruitment data from the Taicang Branch of the Suzhou Blood Center between 2019 and 2024. Multiple machine learning algorithms were employed, including extreme gradient boosting, support vector machine, k-nearest neighbor, logistic regression, decision tree, random forest, and multilayer perceptron. These were combined with techniques such as synthetic minority oversampling, undersampling, and cost-sensitive learning (using MFE and MSFE loss functions). Model parameters were optimized through grid search to identify the best-performing model. Results: In a prospective comparative study against conventional methods, the machine learning models increased the recruitment success rate among high-willingness donors by an average of 129.15%, and the recruitment efficiency per SMS improved by 125.02% compared with the traditional method. Under full-scale SMS sending, the recruitment rate per SMS increased by 42.61%, and SMS sending efficiency improved by 31.77%, significantly enhancing recruitment performance. Conclusion: This study represents the first application of a machine learning-based precision donor recruitment model at the county-level in China. The precise recruitment framework not only improves recruitment efficiency and reduces recruitment costs but also demonstrates strong scalability and generalizability. It provides a scientific and feasible intelligent pathway to ensure the safety and sustainability of the blood supply.

In this work,a rapid and label-free sensing platform was designed for visual detection of p53 gene.The rolling circle amplification(RCA)process of the assay platform was activated by p53 gene to produce long DNA-wires,which could bound with berberine hydrochloride(BBH)and further enhanced its fluorescence.This method showed high sensitivity with a low detection limit of 5.63 pmol/L,and high specificity toward p53 gene over other interference materials,even for single-base mutation gene.The method could realize the visual detection of targets under the illumination of a UV lamp.In addition,the designed fluorescence detection platform was successfully applied to p53 gene analysis in 10% fetal bovine serum samples,and the relative standard deviation and the recoveries were 0.1% -1.2% and 99.5% -104.7%,respectively.This approach had satisfactory characteristics,such as low cost,label-free,rapidity,high sensitivity,good selectivity and anti-interference ability,and reliable detection capability for complex practical samples,demonstrating a promising prospect in the diagnosis and treatment of diseases,especially for cancer.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.