1.Distribution characteristics of pathogens and influencing factors analysis of infections within 90 days after liver transplantation
Huabin PENG ; Haofeng XIONG ; Fei HOU ; Shuang ZHAO ; Yizhi ZHANG ; Tingting CUI ; Zhiying HE ; Jingyi LIU ; Liying SUN
Organ Transplantation 2026;17(2):212-226
Objective To investigate the distribution characteristics of pathogens causing infections within 90 days after liver transplantation and the influencing factors of infection. Methods Clinical data of 176 recipients who underwent liver transplantation at the Liver Transplant Center of Beijing Friendship Hospital Affiliated to Capital Medical University from September 2021 to August 2024 were retrospectively analyzed. Patients were divided into the infection group (n=124) and the non-infection group (n=52) based on whether they developed infection within 90 days after transplantation. The distribution characteristics of pathogens in infected patients were analyzed. Univariate and multivariate logistic regression analyses were used to explore the influencing factors of infection. Results Among the 176 liver transplant recipients, 124 cases developed 243 episodes of 518 bacterial, fungal, viral or mycoplasma infections within 90 days after transplantation, with an overall infection rate of 70.5% (124/176). The composition of pathogens was mainly Gram-negative bacteria (38.6%, 200/518), followed by Gram-positive bacteria (32.2%, 167/518) and viruses (15.4%, 80/518), and fungi accounted for 13.1% (68/518). Among Gram-negative bacteria, the main pathogen was Klebsiella pneumoniae (6.8%, 35/518), and among Gram-positive bacteria, the main pathogen was Enterococcus faecalis (8.5%, 44/518). Viruses included Epstein-Barr virus (3.7%, 19/518) and cytomegalovirus (3.7%, 19/518), and fungi were mainly Candida albicans (6.8%, 35/518). The most common infection site among the 243 episodes was pulmonary infection (42.0%, 102/243), followed by abdominal infection (22.6%, 55/243) and bloodstream infection (18.1%, 44/243). The infections mainly occurred within 2 weeks after transplantation (60.9%, 148/243). Multivariate logistic regression analysis indicated that preoperative infection within 2 weeks, a high preoperative model for end-stage liver disease (MELD) score, and preoperative sarcopenia were independent risk factors for infection within 90 days after liver transplantation (all odds ratio>1, P<0.05). After multivariate correction, the levels of CD4+T cells and CD8+T cells within 90 days after surgery were independently associated with the occurrence of infection. Low levels of CD4+T cells and CD8+T cells might be related to an increased risk of infection. Conclusions The infection rate after liver transplantation is high, and the pathogens are mainly Gram-negative bacteria. The lungs are the most common infection site. Preoperative MELD score, preoperative sarcopenia and preoperative infection within 2 weeks are independent risk factors for infection within 90 days after liver transplantation. Regular monitoring of immune indicators CD4+T cells and CD8+T cells levels after transplantation is helpful to reduce the occurrence of post-transplantation infection.
2.Research and Application of Scalp Surface Laplacian Technique
Rui-Xin LUO ; Si-Ying GUO ; Xin-Yi LI ; Yu-He ZHAO ; Chun-Hou ZHENG ; Min-Peng XU ; Dong MING
Progress in Biochemistry and Biophysics 2025;52(2):425-438
Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.
3.Expert consensus on the prevention and treatment of enamel demineralization in orthodontic treatment.
Lunguo XIA ; Chenchen ZHOU ; Peng MEI ; Zuolin JIN ; Hong HE ; Lin WANG ; Yuxing BAI ; Lili CHEN ; Weiran LI ; Jun WANG ; Min HU ; Jinlin SONG ; Yang CAO ; Yuehua LIU ; Benxiang HOU ; Xi WEI ; Lina NIU ; Haixia LU ; Wensheng MA ; Peijun WANG ; Guirong ZHANG ; Jie GUO ; Zhihua LI ; Haiyan LU ; Liling REN ; Linyu XU ; Xiuping WU ; Yanqin LU ; Jiangtian HU ; Lin YUE ; Xu ZHANG ; Bing FANG
International Journal of Oral Science 2025;17(1):13-13
Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans
;
Consensus
;
Dental Caries/etiology*
;
Dental Enamel/pathology*
;
Tooth Demineralization/etiology*
;
Tooth Remineralization
4.Glutamine signaling specifically activates c-Myc and Mcl-1 to facilitate cancer cell proliferation and survival.
Meng WANG ; Fu-Shen GUO ; Dai-Sen HOU ; Hui-Lu ZHANG ; Xiang-Tian CHEN ; Yan-Xin SHEN ; Zi-Fan GUO ; Zhi-Fang ZHENG ; Yu-Peng HU ; Pei-Zhun DU ; Chen-Ji WANG ; Yan LIN ; Yi-Yuan YUAN ; Shi-Min ZHAO ; Wei XU
Protein & Cell 2025;16(11):968-984
Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism*
;
Myeloid Cell Leukemia Sequence 1 Protein/genetics*
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Humans
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Proto-Oncogene Proteins c-myc/genetics*
;
Cell Proliferation
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Signal Transduction
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Neoplasms/pathology*
;
F-Box-WD Repeat-Containing Protein 7/genetics*
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Cell Survival
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Cell Line, Tumor
;
Apoptosis
5.A review of research methods for elucidating the microstructure of pharmaceutical preparations.
Peng YAN ; Zhiyuan HOU ; Jinsong DING
Journal of Pharmaceutical Analysis 2025;15(5):101156-101156
The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes (CQAs), such as drug release, content uniformity, and stability, which greatly impact the safety and efficacy of drugs. Unlike the inherent molecular structures of active pharmaceutical ingredients (APIs) and excipients, the microstructures of pharmaceutical preparations are developed during the formulation process, presenting unique analytical challenges. In this review, we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations, including X-ray imaging (XRI), scanning electron microscopy (SEM), atomic force microscopy (AFM), Raman spectroscopy, infrared (IR) spectroscopy, and rheometer technology. Subsequently, we highlight the applications, advantages, and limitations of these methods. Finally, we discuss the current challenges and future perspectives in this field. This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations, offering new insights and potential advancements in their development.
6.Study on mechanism of Yourenji Capsules in improving osteoporosis based on network pharmacology and proteomics.
Yun-Hang GAO ; Han LI ; Jian-Liang LI ; Ling SONG ; Teng-Fei CHEN ; Hong-Ping HOU ; Bo PENG ; Peng LI ; Guang-Ping ZHANG
China Journal of Chinese Materia Medica 2025;50(2):515-526
This study aimed to explore the pharmacological mechanism of Yourenji Capsules(YRJ) in improving osteoporosis by combining network pharmacology and proteomics technologies. The SD rats were randomly divided into a blank control group and a 700 mg·kg~(-1) YRJ group. The rats were subjected to gavage administration with the corresponding drugs, and the blank serum, drug-containing serum, and YRJ samples were compared using ultra performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) to analyze the main components absorbed into blood. Network pharmacology analysis was conducted based on the YRJ components absorbed into blood to obtain related targets of the components and target genes involved in osteoporosis, and Venn diagrams were used to identify the intersection of drug action targets and disease targets. The STRING database was used for protein-protein interaction(PPI) network analysis of potential target proteins to construct a PPI network. Gene Ontology(GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment were performed using Enrichr to investigate the potential mechanism of action of YRJ. Ovariectomy(OVX) was performed to establish a rat model of osteoporosis, and the rats were divided into a sham group, a model group, and a 700 mg·kg~(-1) YRJ group. The rats were given the corresponding drugs by gavage. The femurs of the rats were subjected to label-free proteomics analysis to detect differentially expressed proteins, and GO functional enrichment and KEGG pathway enrichment analyses were performed on the differentially expressed proteins. With the help of network pharmacology and proteomics results, the mechanism by which YRJ improves osteoporosis was predicted. The analysis of the YRJ components absorbed into blood revealed 23 bioactive components of YRJ, and network pharmacology results indicated that key targets involved include tumor necrosis factor(TNF), tumor protein p53(TP53), protein kinase(AKT1), and matrix metalloproteinase 9(MMP9). These targets are mainly involved in osteoclast differentiation, estrogen signaling pathways, and nuclear factor-kappa B(NF-κB) signaling pathways. Additionally, the proteomics analysis highlighted important pathways such as peroxisome proliferator-activated receptor(PPAR) signaling pathways, mitogen-activated protein kinase(MAPK) signaling pathways, and β-alanine metabolism. The combined approaches of network pharmacology and proteomics have revealed that the mechanism by which YRJ improves osteoporosis may be closely related to the regulation of inflammation, osteoblast, and osteoclast metabolic pathways. The main pathways involved include the NF-κB signaling pathways, MAPK signaling pathways, and PPAR signaling pathways, among others.
Animals
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Drugs, Chinese Herbal/administration & dosage*
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Osteoporosis/metabolism*
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Proteomics
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Rats
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Rats, Sprague-Dawley
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Network Pharmacology
;
Female
;
Protein Interaction Maps/drug effects*
;
Capsules
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Humans
;
Signal Transduction/drug effects*
7.Alzheimer's disease diagnosis among dementia patients via blood biomarker measurement based on the AT(N) system.
Tianyi WANG ; Li SHANG ; Chenhui MAO ; Longze SHA ; Liling DONG ; Caiyan LIU ; Dan LEI ; Jie LI ; Jie WANG ; Xinying HUANG ; Shanshan CHU ; Wei JIN ; Zhaohui ZHU ; Huimin SUI ; Bo HOU ; Feng FENG ; Bin PENG ; Liying CUI ; Jianyong WANG ; Qi XU ; Jing GAO
Chinese Medical Journal 2025;138(12):1505-1507
8.Investigation and analysis of the current situation of occupational stress of radiation workers in China
Qi ZHANG ; Jianfei LU ; Peng TONG ; Haoran SUN ; Shanshan KOU ; Xiaolan ZHOU ; ·Yusufu AIKEBAIER ; Weiguo ZHU ; Changsong HOU
Chinese Journal of Radiological Health 2025;34(1):46-54
Objective To investigate and analyze the occupational stress levels and influencing factors among radiation workers in China, and provide a reference for alleviating occupational stress and promoting mental health. Methods Using the general situation questionnaire, Effort-Reward Imbalance questionnaire, and radiation protection knowledge questionnaire, a convenience sampling method was adopted to investigate the occupational stress of 243 radiation workers in Liaoning, Fujian, Guangdong, and Xinjiang provinces. The independent samples t-test, one-way analysis of variance, chi-square test, and binary logistic regression were used to analyze the influencing factors. Results The average score of Effort-Reward Imbalance was 0.97 ± 0.22, and 100 (41.15%) radiation workers had occupational stress. There were significant differences in the detection rate of occupational stress among radiation workers of different ages, working years in radiation positions, monthly incomes, daily sleep durations, and daily working hours (P < 0.05). Logistic regression analysis identified daily working hours as a factor contributing to occupational stress. Conclusion The occupational stress among radiation workers in China is relatively severe. It is recommended to pay attention to the associated risks and implement targeted intervention measures to reduce the impact of occupational stress.
10.Phenotypic Function of Legionella pneumophila Type I-F CRISPR-Cas.
Ting MO ; Hong Yu REN ; Xian Xian ZHANG ; Yun Wei LU ; Zhong Qiu TENG ; Xue ZHANG ; Lu Peng DAI ; Ling HOU ; Na ZHAO ; Jia HE ; Tian QIN
Biomedical and Environmental Sciences 2025;38(9):1105-1119
OBJECTIVE:
CRISPR-Cas protects bacteria from exogenous DNA invasion and is associated with bacterial biofilm formation and pathogenicity.
METHODS:
We analyzed the type I-F CRISPR-Cas system of Legionella pneumophila WX48, including Cas1, Cas2-Cas3, Csy1, Csy2, Csy3, and Cas6f, along with downstream CRISPR arrays. We explored the effects of the CRISPR-Cas system on the in vitro growth, biofilm-forming ability, and pathogenicity of L. pneumophila through constructing gene deletion mutants.
RESULTS:
The type I-F CRISPR-Cas system did not affect the in vitro growth of wild-type or mutant strains. The biofilm formation and intracellular proliferation of the mutant strains were weaker than those of the wild type owing to the regulation of type IV pili and Dot/Icm type IV secretion systems. In particular, Cas6f deletion strongly inhibited these processes.
CONCLUSION
The type I-F CRISPR-Cas system may reduce biofilm formation and intracellular proliferation in L. pneumophila.
Legionella pneumophila/pathogenicity*
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CRISPR-Cas Systems
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Biofilms/growth & development*
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Phenotype
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Bacterial Proteins/metabolism*
;
Gene Deletion

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