ObjectiveTo explore the effect of serum containing Zhenwutang on myocardial mast cell apoptosis induced by angiotensin Ⅱ （AngⅡ） and the mechanism of the correlation between apoptosis and mitochondrial autophagy. MethodsIn this experiment， AngⅡ and serum containing Zhenwutang with different concentrations were used to interfere with H9C2 cardiomyocytes for 24 h， and the survival rate of H9C2 cardiomyocytes was detected by cell counting kit-8 （CCK-8） to screen the optimal concentration for the experiment. Enzyme-linked immunosorbent assay （ELISA） was used to detect the content of B-type natriuretic peptide （BNP） in cell culture supernatant， and immunofluorescence was used to detect the cell surface area to verify the construction of the myocardial mast cell model. Subsequently， the experiment was divided into a blank group （20% blank serum）， a model group （20% blank serum + 5×10^-5 mol·L^-1 AngⅡ）， low-， medium-， and high-dose （5%， 10% and 20%） serum containing Zhenwutang groups， an autophagy inhibitor group （1×10^-4 mol·L^-1 3-MA）， and autophagy inducer group （1×10^-7 mol·L^-1 rapamycin）. The apoptosis level of H9C2 cells and the changes of mitochondrial membrane potential were detected by flow cytometry. The lysosomal probe （Lyso Tracker） and mitochondrial probe （Mito Tracker） co-localization was employed to detect autophagy. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect Caspase-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， Bcl-2-related X protein （Bax）， and cytochrome C （Cyt C） in apoptosis-related pathways and the relative mRNA expression of ubiquitin ligase （Parkin）， phosphatase and tensin homolog （PTEN）-induced kinase 1 （PINK1）， and p62 protein in mitochondrial autophagy-related pathways. Western blot was used to detect cleaved Caspase-3， cleaved Caspase-9， Bax， Bcl-2， and Cyt C in apoptosis-related pathways， phosphorylated ubiquitin ligase （p-Parkin）， phosphorylated PTEN-induced kinase 1 （p-PINK1）， p62， and Bcl-2 homology domain protein Beclin1 in mitochondrial autophagy-related pathways， and the change of microtubule-associated protein 1 light chain 3 （LC3） Ⅱ/Ⅰ ratio. ResultsCCK-8 showed that when the concentration of AngⅡ was 5×10^-5 mol·L^-1， the cell activity was the lowest， and there was no cytotoxicity. At this concentration， the surface area of cardiomyocytes was significantly increased （P<0.01）， and the content of BNP in the supernatant of culture medium was significantly increased （P<0.05）. Therefore， AngⅡ with a concentration of 5×10^-5 mol·L^-1 was selected for the subsequent modeling of myocardial mast cells. Compared with the blank group， the model group and the autophagy inhibitor 3-MA group had a significantly increased apoptosis rate （P<0.01） and significantly decreased mitochondrial membrane potential （P<0.01）. The results of immunofluorescence co-localization showed that compared with the blank group， the model group had a significantly decreased number of red and green fluorescence spots. The results of Real-time PCR showed that compared with that in the blank group， the relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 in the model group was significantly up-regulated （P<0.01）， while the relative mRNA expression of Bcl-2， Parkin， and PINK1 was significantly down-regulated （P<0.01）. In addition， the relative protein expression of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 was significantly up-regulated （P<0.01）. The LC3Ⅱ/Ⅰ was significantly decreased， and the relative protein expression of Bcl-2， p-Parkin， p-PINK1， and Beclin1 was significantly down-regulated （P<0.01）. Compared with the model group， the serum containing Zhenwutang groups and the autophagy inducer group had significantly decreased apoptosis rate （P<0.01）， and the decrease ratio of mitochondrial membrane potential is significantly lowered （P<0.01） in a dose-dependent manner. Additionally， both red and green fluorescence spots became more in these groups. In the 3-MA group， the number of red and green fluorescence spots decreased significantly. The relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 was significantly down-regulated （P<0.05， P<0.01）， while that of Bcl-2， Parkin， and PINK1 was significantly up-regulated （P<0.01）. In the serum containing Zhenwutang groups， the relative protein expression levels of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 were significantly down-regulated （P<0.05，P<0.01）. The LC3Ⅱ/Ⅰ was significantly increased， and the relative protein expression levels of Bcl-2， p-Parkin， p-PINK1， and Beclin1 were significantly up-regulated （P<0.01）. ConclusionThe serum containing Zhenwutang can reduce the apoptosis of myocardial mast cells and increase mitochondrial autophagy. This is related to the inhibition of intracellular Bax/Bcl-2/Caspase-3 apoptosis pathway and regulation of Parkin/PINK1 mitochondrial autophagy pathway.

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

During transfer tasks, the dual-arm nursing-care robot require a human-robot mechanics model to determine the balance region to support the patient safely and stably. Previous studies utilized human-robot two-dimensional static equilibrium models, ignoring the human body volume and muscle torques, which decreased model accuracy and confined the robot ability to adjust the patient's posture in three-dimensional spatial. Therefore, this study proposes a three-dimensional spatial mechanics modeling method based on individualized human musculoskeletal multibody dynamics. Firstly, based on the mechanical features of dual-arm support, this study constructed a foundational three-dimensional human-robot mechanics model including body posture, contact position and body force. With the computed tomography data from subjects, a three-dimensional femur-pelvis-sacrum model was reconstructed, and the individualized musculoskeletal dynamics was analyzed using the ergonomics software, which derived the human joint forces and completed the mechanic model. Then, this study established a dual-arm robot transfer platform to conduct subject transfer experiments, showing that the constructed mechanics model possessed higher accuracy than previous methods. In summary, this study provides a three-dimensional human-robot mechanics model adapting to individual transfers, which has potential application in various scenarios such as nursing-care and rehabilitating robots.
Humans ; Robotics ; Biomechanical Phenomena ; Posture ; Imaging, Three-Dimensional ; Nursing Care

OBJECTIVE: To explore clinical efficacy of membrane-induced technique combined with gastrocnemius muscle flap transposition in treating traumatic osteomyelitis of the upper tibia. METHODS: A retrospective analysis was conducted on 7 patients with traumatic osteomyelitis of the upper tibia who were treated with membrane-induced technique combined with gastrocnemius muscle flap transposition from January 2022 to December 2023. Among them, there were 4 males and 3 females; aged from 29 to 57 years old; 4 patients were treated after open fracture, 2 patients were treated after closed fracture, and 1 patient was treated after scalding; the courses of disease ranges from 2 weeks to 8 years; sinus tracts were present in all patients, and the lesion range of the tibia ranged from 5 to 9 cm. The results of deep tissue bacterial culture showed that 2 patients were negative, 3 patients were staphylococcus aureus, 1 patient was methicillin-resistant staphylococcus aureus, and 1 patient was pseudomonas aeruginosa and 1 patient was klebsiella pneumoniae. After debridement, the range of bone defect ranged from 8 to 12 cm, and the cortical defect accounted for approximately 30% of the circumference. The area of soft tissue defect ranged from 8.0 cm×2.0 cm to 10.0 cm×6.0 cm. At the first stage, vancomycin-loaded/meropenem/gentamicin-loaded bone cement was implanted. The gastrocnemius muscle flap was repositioned to cover the wound surface and free skin grafting was performed. After an interval of 7 to 10 weeks, the stageⅡsurgery was performed to remove bone cement. Autologous iliac bone mixed with vancomycin/gentamicin and calcium sulfate artificial bone was transplanted, and the wound was sutured. One patient retained the original internal plants, one patient removed the internal plants and replaced them with steel plate external fixation, one patient replaced the internal plants and added steel plate external fixation, and three patients were simply fixed with steel plate external fixation. One year after operation, the recovery of knee joint and ankle joint functions was evaluated by using Hospital for Special Surgery (HSS) knee joint score and Kofoed ankle joint function score respectively. RESULTS: All patients had their wounds closed simultaneously with bone cement implantation and healed well. All patients were followed up for 12 to 17 months after operation, and satisfactory bone healing was achieved at 6 months after stageⅡsurgery. Twelve months after operation, all patients had good bone healing without obvious limping was observed when walking. At 12 months after operation HSS knee joint score ranged from 93 to 100 points, and Kofoed ankle function score ranged from 96 to 100 points. CONCLUSION For traumatic osteomyelitis of the upper tibia, a staged treatment plan combining membrane-induced technique and gastrocnemius flap transposition on the basis of thorough debridement could safely cover the wound surface, effectively control bone infection and achieve satisfactory bone healing, without adverse effects on limb function.
Humans ; Male ; Female ; Middle Aged ; Osteomyelitis/surgery* ; Adult ; Surgical Flaps ; Retrospective Studies ; Tibia/injuries* ; Muscle, Skeletal/surgery*

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

OBJECTIVES: To explore the relationship between white matter injury (WMI) and cerebral perfusion in preterm infants using arterial spin labeling (ASL). METHODS: A total of 293 preterm infants (gestational age <34 weeks) hospitalized at the Third Affiliated Hospital of Zhengzhou University between June 2022 and June 2024 were included. After achieving clinical stability, the infants underwent brain magnetic resonance imaging (MRI) and ASL. Based on MRI findings, infants were classified into WMI (n=66) and non-WMI (n=227) groups. Cerebral perfusion parameters were compared between groups, and the association between WMI and perfusion alterations was evaluated. RESULTS: The WMI group showed a higher incidence of mild intraventricular hemorrhage (IVH) than the non-WMI group (P<0.05). Significantly lower cerebral perfusion was observed in the WMI group across bilateral frontal, temporal, parietal, and occipital lobes, as well as the basal ganglia and thalamus (P<0.05). After adjusting for gestational age, corrected gestational age at ASL scan, and mild IVH, WMI remained significantly associated with reduced regional perfusion (P<0.05). CONCLUSIONS WMI in preterm infants correlates with localized cerebral hypoperfusion. ASL-detected perfusion abnormalities may provide novel insights into WMI pathogenesis.
Humans ; White Matter/blood supply* ; Infant, Newborn ; Spin Labels ; Infant, Premature ; Female ; Male ; Cerebrovascular Circulation ; Magnetic Resonance Imaging

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

Objective To investigate the species of ticks in Suizhou City, Hubei Province, so as to provide insights into management of ticks and tick-borne diseases. Methods During the period between May 2023 and June 2024, livestock breeding farms and vegetation neighboring the place of residence of confirmed and suspected patients with tick-borne disease were selected as sampling points in rural areas from Yindian Township, Gaocheng Township, Wanhe Township, Wushan Township, Xiaolin Township, Xihe Township, Hedian Township and Beijiao Street in Suizhou City, Hubei Province, where confirmed and suspected cases with tick-borne diseases had been reported. The parasitic ticks on the body surface of free-range livestock were captured with tweezers in livestock breeding farms, and free ticks on the vegetation surface were captured with the flagging method. Morphological identification of tick samples was performed under a microscope, and the gender and developmental stage of ticks were determined. One engorged adult tick, 2 to 3 blood-feeding but non-engorged adult ticks, 10 to 15 unfed female ticks, 15 to 20 unfed male ticks, and 30 to 40 tick nymphs or larvae were assigned into a group, respectively. Genomic DNA was extracted from tick samples in each group, and mitochondrial 16S rRNA gene was amplified. Sequence analysis was performed with the DNASTAR software, and phylogenetic analysis was performed using the software MEGA 7.0. In addition, the phylogenetic tree was generated using the maximum likelihood method based on the Kimura 2 parameter model. Results A total of 2 438 ticks were captured from Suizhou City, Hubei Province during the period between May 2023 and June 2024, including 595 free ticks and 1 483 parasitic ticks. Three developmental stages of ticks were captured, including larvae, nymphs, and adults, and 75.18% (1 899/2 438) of captured ticks were adult, in which 79.04% (1 501/1 899) were female. Morphological and molecular biological assays identified one family, three genera and four species of captured ticks, including 2 425 Haemaphysalis longicornis ticks (99.47%) and one H. flava tick (0.04%) of the genus Haemaphysalis, 11 Rhipicephalus microplus ticks (0.45%) of the genus Rhipicephalus, and one Ixodes sinensis tick (0.04%) of the genus Ixodes in the family Ixodidae. Phylogenetic analysis revealed that the H. longicornis sequence (SZ49) in this study was clustered with sequences from Yunnan Province (GenBank accession number: MH024510.1), Hebei Province (GenBank accession number: MK450606.1) and Henan Province (GenBank accession number: MZ230645.1) into a clade, and the H. flava sequence (SZ19) in this study was clustered with sequences from Japan (GenBank accession number: MW064044.1), South Korea (GenBank accession number: ON629585.1), and Jiangsu Province (GenBank accession number: PP494741.1) and Hebei Province of China (GenBank accession number: MH520685.1) into a clade, while the R. microplus sequence (SZ8) in this study was clustered with the sequences from India (GenBank accession number: MK621328.1), and Henan Province (GenBank accession number: MT555307.1) and Guizhou Province of China (GenBank accession number: PP446801.1) into a clade. The sequence of I. sinensis (SZ23) in this study had 99.51% homology with that (GenBank accession number: OM368265.1) of ticks sampled from Wuhan City, Hubei Province. Conclusion There are four tick species of H. longicornis, H. flava, R. microplus and I. sinensis in Suizhou City, Hubei Province, and H. longicornis is the dominant species. H. flava is firstly recorded in Suizhou City.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.