1.The Diversity of Filamentous Morphologies and Magnetic Sensitivity Modulated by Diverse MagR Expression in Bacteria
Ya-Fei CHANG ; Jing ZHANG ; Peng ZHANG ; Xiu-Juan ZHOU ; Meng-Ke WEI ; Tian-Tian CAI ; Pei-Qi HE ; Jun-Feng WANG ; Can XIE
Progress in Biochemistry and Biophysics 2026;53(5):1439-1456
Objective Magnetoreception, the remarkable ability of diverse animals to sense and utilize the geomagnetic field for orientation and navigation, remains a molecularly unresolved mystery in sensory biology. The putative magnetoreceptor (MagR, previously known as IscA1) is a highly conserved iron-sulfur protein implicated in both magnetoreception and iron metabolism; however, the functional diversity among its cross-species homologs remains poorly understood. Cellular morphology is a key genetically determined trait that can be altered through genetic or environmental modifications—a process known as cell morphology engineering. Constructing engineered cells with specific morphological features and magnetic sensitivity to achieve remote, non-invasive magnetic modulation represents a crucial goal in this field with significant application potential. Therefore, this study aims to systematically investigate the effects of MagR heterologous expression on bacterial morphology and magnetic sensing capabilities, screen for MagR-based magnetically sensitive morphology engineering pathways, and reveal the underlying molecular mechanisms. Methods We systematically screened 28 MagR homologous genes from diverse prokaryotic and animal taxa to evaluate their expression and corresponding phenotypic effects in Escherichia coli (E. coli). To compare the differential magnetic responses among bacteria expressing various recombinant MagR proteins, we utilized high-throughput automated bright-field microscopic imaging and scanning electron microscopy (SEM). Furthermore, comprehensive biochemical and biophysical characterizations of iron and iron-sulfur cluster binding were performed using Ferrozine colorimetric assays, electron paramagnetic resonance (EPR) spectroscopy, ultraviolet-visible (UV-Vis) absorption, and circular dichroism (CD) spectroscopy. Additionally, 100 mT static magnetic field (SMF) exposure experiments were conducted to assess magnetically tunable phenotypes, while the intrinsic magnetic properties of purified MagR proteins were directly measured using a superconducting quantum interference device (SQUID) magnetometer. Results Our results demonstrated that the heterologous expression of MagR homologs induced varying degrees of bacterial filamentation. From this comprehensive screen, two distinct morphological patterns were identified: hydra (Hydra vulgaris) MagR (hyMagR) promoted uniform cell elongation and filamentation, exhibiting robust magnetic sensitivity manifested as significantly enhanced filamentation under the 100 mT SMF. In contrast, pigeon (Columba livia) MagR (clMagR) induced only low-frequency, extreme filamentation (sporadically exceeding 80 μm) with a relatively weaker magnetic morphological response. Mechanistically, our data unambiguously proved that these phenotypic differences are primarily driven by distinct iron redox preferences rather than total cellular iron accumulation. Specifically, hyMagR preferentially binds ferrous iron (Fe2+), whereas clMagR favors ferric iron (Fe3+) and forms more stable iron-sulfur clusters. Intriguingly, although SQUID magnetometry showed that purified clMagR exhibited approximately five-fold higher mass magnetic susceptibility than hyMagR, its cellular magnetic response was weaker. We hypothesize that the Fe2+-preferred intracellular environment associated with hyMagR overexpression primes the cell for enhanced generation of reactive oxygen species (ROS) via the Fenton reaction. Exposure to an SMF synergizes with this primed redox state, triggering the bacterial SOS response and upregulating cell division inhibitors to efficiently induce uniform filamentation. Conclusion Our findings identify the Fe2+/Fe3+ redox state as a critical determinant of MagR-mediated morphological remodeling and magnetic responsiveness. This discovery suggests a potential strategy for engineering magnetically responsive cellular systems for synthetic biology applications, and provides a plausible framework, which potentially combines intrinsic protein magnetism with redox-state modulation, for further investigating the evolutionary mechanisms of MagR-mediated magnetoreception.
2.The Diversity of Filamentous Morphologies and Magnetic Sensitivity Modulated by Diverse MagR Expression in Bacteria
Ya-Fei CHANG ; Jing ZHANG ; Peng ZHANG ; Xiu-Juan ZHOU ; Meng-Ke WEI ; Tian-Tian CAI ; Pei-Qi HE ; Jun-Feng WANG ; Can XIE
Progress in Biochemistry and Biophysics 2026;53(5):1439-1456
Objective Magnetoreception, the remarkable ability of diverse animals to sense and utilize the geomagnetic field for orientation and navigation, remains a molecularly unresolved mystery in sensory biology. The putative magnetoreceptor (MagR, previously known as IscA1) is a highly conserved iron-sulfur protein implicated in both magnetoreception and iron metabolism; however, the functional diversity among its cross-species homologs remains poorly understood. Cellular morphology is a key genetically determined trait that can be altered through genetic or environmental modifications—a process known as cell morphology engineering. Constructing engineered cells with specific morphological features and magnetic sensitivity to achieve remote, non-invasive magnetic modulation represents a crucial goal in this field with significant application potential. Therefore, this study aims to systematically investigate the effects of MagR heterologous expression on bacterial morphology and magnetic sensing capabilities, screen for MagR-based magnetically sensitive morphology engineering pathways, and reveal the underlying molecular mechanisms. Methods We systematically screened 28 MagR homologous genes from diverse prokaryotic and animal taxa to evaluate their expression and corresponding phenotypic effects in Escherichia coli (E. coli). To compare the differential magnetic responses among bacteria expressing various recombinant MagR proteins, we utilized high-throughput automated bright-field microscopic imaging and scanning electron microscopy (SEM). Furthermore, comprehensive biochemical and biophysical characterizations of iron and iron-sulfur cluster binding were performed using Ferrozine colorimetric assays, electron paramagnetic resonance (EPR) spectroscopy, ultraviolet-visible (UV-Vis) absorption, and circular dichroism (CD) spectroscopy. Additionally, 100 mT static magnetic field (SMF) exposure experiments were conducted to assess magnetically tunable phenotypes, while the intrinsic magnetic properties of purified MagR proteins were directly measured using a superconducting quantum interference device (SQUID) magnetometer. Results Our results demonstrated that the heterologous expression of MagR homologs induced varying degrees of bacterial filamentation. From this comprehensive screen, two distinct morphological patterns were identified: hydra (Hydra vulgaris) MagR (hyMagR) promoted uniform cell elongation and filamentation, exhibiting robust magnetic sensitivity manifested as significantly enhanced filamentation under the 100 mT SMF. In contrast, pigeon (Columba livia) MagR (clMagR) induced only low-frequency, extreme filamentation (sporadically exceeding 80 μm) with a relatively weaker magnetic morphological response. Mechanistically, our data unambiguously proved that these phenotypic differences are primarily driven by distinct iron redox preferences rather than total cellular iron accumulation. Specifically, hyMagR preferentially binds ferrous iron (Fe2+), whereas clMagR favors ferric iron (Fe3+) and forms more stable iron-sulfur clusters. Intriguingly, although SQUID magnetometry showed that purified clMagR exhibited approximately five-fold higher mass magnetic susceptibility than hyMagR, its cellular magnetic response was weaker. We hypothesize that the Fe2+-preferred intracellular environment associated with hyMagR overexpression primes the cell for enhanced generation of reactive oxygen species (ROS) via the Fenton reaction. Exposure to an SMF synergizes with this primed redox state, triggering the bacterial SOS response and upregulating cell division inhibitors to efficiently induce uniform filamentation. Conclusion Our findings identify the Fe2+/Fe3+ redox state as a critical determinant of MagR-mediated morphological remodeling and magnetic responsiveness. This discovery suggests a potential strategy for engineering magnetically responsive cellular systems for synthetic biology applications, and provides a plausible framework, which potentially combines intrinsic protein magnetism with redox-state modulation, for further investigating the evolutionary mechanisms of MagR-mediated magnetoreception.
3.Role of artificial intelligence in medical image analysis.
Lu WANG ; Shimin ZHANG ; Nan XU ; Qianqian HE ; Yuming ZHU ; Zhihui CHANG ; Yanan WU ; Huihan WANG ; Shouliang QI ; Lina ZHANG ; Yu SHI ; Xiujuan QU ; Xin ZHOU ; Jiangdian SONG
Chinese Medical Journal 2025;138(22):2879-2894
With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence
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Humans
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Image Processing, Computer-Assisted/methods*
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Neural Networks, Computer
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Deep Learning
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Diagnostic Imaging/methods*
4.Data mining of current research status of clinical trial drug management in China by bibliometrics
Chang XU ; Xinna ZHOU ; Lu QI ; Yu WANG ; Xinghe WANG
Journal of Pharmaceutical Practice and Service 2025;43(8):404-409
Objective To clarify the current development status and research hotspots in the field of experimental drug management in China through data mining by bibliometric. Methods Key words such as “experiment”, “drug”, and “management” were used to search the Chinese literature in China National Knowledge Infrastructure (CNKI). The title, author name, author affiliation, Chinese abstract, Chinese keywords, publication period, journal name, and other content of the literature were extracted from the literature. Cluster analysis was performed by CNKI literature visualization analysis system, CiteSpace and other software, and a network knowledge map was drawn. Results The literature in the field of experimental drug management in China was first published in 1994, and a total of 140 articles were published until 2022. Among them, 20 articles were supported by relevant funds, and the keyword co-occurrence frequency was highest among “subjects”. The most frequently published medium was the Chinese Pharmacological Yearbook. Conclusion At present, the quantity and quality of literature in the field of experimental drug management in China were relatively small, and the cooperation and communication among authors were not close. The funding from various fund projects in this field was also lacking. These factors led to a lower overall development level and slower development speed in this field.
5.Establishment and Validation of Prognostic Model for Aging-related Genes of Squamous Cell Lung Cancer Based on TCGA Database
Yu-lin HE ; Shao-zhang ZHOU ; Qi-chang HUANG ; Tian GUO
Progress in Modern Biomedicine 2025;25(17):2729-2739
Objective:To investigate the role of aging-related genes(ARGs)in the prognosis of lung squamous cell carcinoma(LUSC)and establish a novel prognostic prediction model.Methods:Transcriptomic data and clinical information of LUSC patients were obtained from TCGA,combined with ARGs from Aging Atlas.Key genes were screened through differential expression analysis,survival analysis,and Cox regression to construct a prognostic model.Model performance was validated in clinical subgroups,and biological pathway enrichment(GSEA)and immune microenvironment analyses were performed.Results:Five ARGs(ERFFI1,MDH1,SENP2,SNAI1,TP63)were identified to build the model.Significant survival differences were observed between high-and low-risk groups(P<0.001),with 1-,3-,and 5-year AUC values of 0.610,0.668,and 0.665,respectively.The risk score was an independent prognostic factor(HR=11.261,95%CI:3.654-34.701,P<0.001)and showed predictive efficacy in both early-stage(Ⅰ-Ⅱ,P=0.022)and advanced-stage(Ⅲ-Ⅳ,P=0.004)patients.GSEA revealed significant enrichment of Alzheimer's disease(P=0.003)and cell adhesion pathways(P=0.008)in high-risk groups.SNAI1 correlated positively with M1/M2 macrophage infiltration(r=0.45,P<0.001),MDH1 associated with 12 immune cell types(|r|>0.3,P<0.05),and the risk score linked to CD8+T cells(r=0.38)and M2 macrophages(r=0.32)(both P<0.001).Twenty-three immune checkpoints(e.g.,TNFRSF14,CD200R1)were differentially expressed between groups and survival-related(P<0.05).High-risk patients exhibited elevated TIDE scores(P<0.001),indicating enhanced immune suppression.Conclusion:This model provides a novel tool for LUSC prognosis assessment,but further clinical validation is required.
6.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
7.Establishment and Validation of Prognostic Model for Aging-related Genes of Squamous Cell Lung Cancer Based on TCGA Database
Yu-lin HE ; Shao-zhang ZHOU ; Qi-chang HUANG ; Tian GUO
Progress in Modern Biomedicine 2025;25(17):2729-2739
Objective:To investigate the role of aging-related genes(ARGs)in the prognosis of lung squamous cell carcinoma(LUSC)and establish a novel prognostic prediction model.Methods:Transcriptomic data and clinical information of LUSC patients were obtained from TCGA,combined with ARGs from Aging Atlas.Key genes were screened through differential expression analysis,survival analysis,and Cox regression to construct a prognostic model.Model performance was validated in clinical subgroups,and biological pathway enrichment(GSEA)and immune microenvironment analyses were performed.Results:Five ARGs(ERFFI1,MDH1,SENP2,SNAI1,TP63)were identified to build the model.Significant survival differences were observed between high-and low-risk groups(P<0.001),with 1-,3-,and 5-year AUC values of 0.610,0.668,and 0.665,respectively.The risk score was an independent prognostic factor(HR=11.261,95%CI:3.654-34.701,P<0.001)and showed predictive efficacy in both early-stage(Ⅰ-Ⅱ,P=0.022)and advanced-stage(Ⅲ-Ⅳ,P=0.004)patients.GSEA revealed significant enrichment of Alzheimer's disease(P=0.003)and cell adhesion pathways(P=0.008)in high-risk groups.SNAI1 correlated positively with M1/M2 macrophage infiltration(r=0.45,P<0.001),MDH1 associated with 12 immune cell types(|r|>0.3,P<0.05),and the risk score linked to CD8+T cells(r=0.38)and M2 macrophages(r=0.32)(both P<0.001).Twenty-three immune checkpoints(e.g.,TNFRSF14,CD200R1)were differentially expressed between groups and survival-related(P<0.05).High-risk patients exhibited elevated TIDE scores(P<0.001),indicating enhanced immune suppression.Conclusion:This model provides a novel tool for LUSC prognosis assessment,but further clinical validation is required.
8.Treatment plan optimization for intensity-modulated brachytherapy based on the conjugate gradient algorithm
Miao QI ; Junyi LIU ; Shijun LI ; Yankui CHANG ; Jieping ZHOU ; Bing YAN ; Yong CHENG ; Aidong WU ; Xi PEI ; Xie XU
Chinese Journal of Radiological Medicine and Protection 2025;45(1):56-62
Objective:To investigate the application of the conjugate gradient (CG) algorithm to treatment plan optimization for intensity-modulated brachytherapy (IMBT).Methods:The general Monte Carlo software TOPAS was utilized to simulate the 192Ir source of IMBT, and the unit dose contribution matrix was calculated. An objective function was established using the weighted least squares method and was solved using the CG algorithm to achieve optimized IMBT treatment plans. The optimization was validated using five clinical cervical cancer cases under modulation width 60°. The dose distributions of IMBT treatment plans under 45°, 60°, 90°, 120°, and 180° modulation widths were compared using the Wilcoxon test to determine the optimal IMBT treatment plan for cervical cancer treatment. Results:The CG algorithm successfully optimized IMBT treatment plans under modulation width 60° for five cases within 22.2 s on average. On the premise of sufficient target dose coverage, the average D2 cm 3 values of the bladder and rectum in IMBT treatment plans were 3.66 and 1.97 Gy, respectively, representing reductions of 0.54 and 0.69 Gy compared to traditional brachytherapy plans. For the five modulation widths, the D90% values of all IMBT treatment plans reached 6 Gy, without statistically significant differences ( P > 0.05). The average D2 cm 3 values of the bladder in IMBT treatment plans were significantly lower than those in the traditional brachytherapy plans( P<0.05), with modulation width 60° associated with the greatest reduction of 0.61 Gy. In contrast, the average D2 cm 3 values of the rectum under 45°, 60°, and 90° modulation widths decreased by 0.63, 0.54, and 0.45 Gy, respectively, compared to traditional plans, with statistically significant differences( P<0.05). Conclusions:The CG method enables rapid achievement of optimized IMBT treatment plans that meet clinical requirements, and modulation width 60° contributes to valid dosimetric optimization. This study can serve as a guide for the clinical implementation of IMBT.
9.Prevotella nigrescens exacerbates periodontal inflammation and impairs cognitive function in mice
Qi CHEN ; Tiantian XIA ; Yongqiang ZHOU ; Mingyang CHANG ; Nan HU ; Yanmei YANG ; Zhong LI ; Yue GAO ; Bin GU
Journal of Southern Medical University 2025;45(3):453-460
Objective To investigate the effects of periodontitis induced by Prevotella nigrescens(Pn)combined with ligation on cognitive functions in mice.Methods Twenty-four C57BL/6J mice were randomly divided into control group,ligation group,and ligation+Pn treatment(P+Pn)group.Experimental periodontitis was induced by silk ligation of the first molars followed by topical application of Pn for 6 weeks.After modeling,alveolar bone resorption was assessed using micro-CT and histological analysis.Learning and memory abilities of the mice were evaluated using open field test(OFT),novel object recognition test(NORT),and Morris water maze test(MWM).Seven weeks after the start of modeling,the mice were sacrificed for examining histopathological changes in the hippocampus using HE and Nissl staining.Results After 6 weeks of molar ligation,micro-CT revealed horizontal alveolar bone resorption and furcation exposure in the mice,and histological analysis showed apical migration of the junctional epithelium,epithelial ridge hyperplasia,and lymphocyte infiltration,and these changes were obviously worsened in P+Pn group.Alveolar bone height decreased significantly in both ligation groups compared to the control group.Cognitive tests showed that the mice in both of the ligation groups traveled shorter distances in OFT,showed reduced novel object preference in NORT,and exhibited longer escape latencies in MWM,and the mice in P+Pn group had significantly poorer performances in the tests.Histologically,obvious neuronal cytoplasmic degeneration,necrosis,nuclear pyknosis,vacuolation,and reduced Nissl bodies and viable neurons were observed in the hippocampal regions of the mice in the two ligation groups.Conclusion Pn infection aggravates alveolar bone destruction,accelerates necrosis and causes morphological abnormalities of neuronal cells in the hippocampus to reduce cognitive functions of mice with periodontitis.
10.Treatment plan optimization for intensity-modulated brachytherapy based on the conjugate gradient algorithm
Miao QI ; Junyi LIU ; Shijun LI ; Yankui CHANG ; Jieping ZHOU ; Bing YAN ; Yong CHENG ; Aidong WU ; Xi PEI ; Xie XU
Chinese Journal of Radiological Medicine and Protection 2025;45(1):56-62
Objective:To investigate the application of the conjugate gradient (CG) algorithm to treatment plan optimization for intensity-modulated brachytherapy (IMBT).Methods:The general Monte Carlo software TOPAS was utilized to simulate the 192Ir source of IMBT, and the unit dose contribution matrix was calculated. An objective function was established using the weighted least squares method and was solved using the CG algorithm to achieve optimized IMBT treatment plans. The optimization was validated using five clinical cervical cancer cases under modulation width 60°. The dose distributions of IMBT treatment plans under 45°, 60°, 90°, 120°, and 180° modulation widths were compared using the Wilcoxon test to determine the optimal IMBT treatment plan for cervical cancer treatment. Results:The CG algorithm successfully optimized IMBT treatment plans under modulation width 60° for five cases within 22.2 s on average. On the premise of sufficient target dose coverage, the average D2 cm 3 values of the bladder and rectum in IMBT treatment plans were 3.66 and 1.97 Gy, respectively, representing reductions of 0.54 and 0.69 Gy compared to traditional brachytherapy plans. For the five modulation widths, the D90% values of all IMBT treatment plans reached 6 Gy, without statistically significant differences ( P > 0.05). The average D2 cm 3 values of the bladder in IMBT treatment plans were significantly lower than those in the traditional brachytherapy plans( P<0.05), with modulation width 60° associated with the greatest reduction of 0.61 Gy. In contrast, the average D2 cm 3 values of the rectum under 45°, 60°, and 90° modulation widths decreased by 0.63, 0.54, and 0.45 Gy, respectively, compared to traditional plans, with statistically significant differences( P<0.05). Conclusions:The CG method enables rapid achievement of optimized IMBT treatment plans that meet clinical requirements, and modulation width 60° contributes to valid dosimetric optimization. This study can serve as a guide for the clinical implementation of IMBT.

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