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.

Objective To identify potential immunosenescence markers in benign prostatic hyperplasia(BPH)and to explore BPH-related senescent phenotypes. Methods Three transcriptome datasets and one single-cell RNA-sequencing(scRNA-seq)dataset for BPH and normal prostate tissues were obtained from the Gene Expression Omnibus(GEO)database. The GSE7307 and GSE119195 were combined to analyze differentially expressed genes(DEGs). Enrichment analysis and immune infiltration analysis were used to explore aging-related changes in the immune microenvironment. Weighted gene coexpression network analysis(WGCNA)was applied to identify immune-related genes in GSE132714. ScRNA-seq data were employed to investigate the transcriptomic landscape, luminal cell heterogeneity, and aging-related alterations in BPH through cell-cell communication and pseudotime analysis. Finally, the results were validated with in vitro experiments. Results A total of 1202 DEGs and 627 immune-related genes were identified in BPH and normal prostate tissues. Enrichment analysis indicated that the vascular endothelial growth factor(VEGF)signaling pathway exhibited a downregulated aging phenotype in BPH. In scRNA-seq analysis, 9 cell types were identified. The VEGF signaling pathway in BPH exhibited an aging-related expression pattern, characterized by decreased vascular endothelial growth factor A(VEGFA)in luminal cells. Conclusion Our study identified VEGFA as a marker of immunosenescence in BPH, with changes of the VEGF pathway. Meanwhile, low expression of VEGFA, coupled with high expression of placental growth factor(PlGF)and vascular endothelial growth factor receptor(VEGFR), represented a senescent phenotype of the prostate.

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.

Objective:To investigate the clinical diagnosis,treatment and prognosis of traumatic ectopic testis with torsion.Methods:We retrospectively analyzed the clinical data on a case of traumatic ectopic testis with torsion and reviewed relevant litera-ture.Results:After diagnosed with traumatic ectopic testis with torsion,the patient underwent exploratory operation for confirmation of orchiocatabasis,followed by testicular reduction and fixation.Follow-up visit at 1 month after surgery showed good blood supply and no obvious testicular atrophy.Conclusion:Traumatic ectopic testis with torsion is an extremely rare emergency condition,for which color Doppler ultrasonography is an effective means of examination.Once suspected of or confirmed with the problem,the patient should receive exploratory surgery,testicular reduction and fixation within 6 hours,and close postoperative observation.

AIM To compare total sugar,total protein,total phenol,total flavonoid,calycosin-7-O-β-D-glucoside,liquiritin,lobetyolin,quercetin,isoferulic acid,hesperidin,glycyrrhizic acid contents and their antioxidant activities,hypoglycemic activities of big honey pill,small honey pill,water pill,concentrated pill,granule,mixture and decoction of Buzhong Yiqi Recipe.METHODS Anthraquinone-sulfuric acid method,Coomassie brilliant blue method,Folin-phenol colorimetry method,sodium nitrite-aluminum nitrate method and HPLC were adopted in the content determination of total sugar,total protein,total phenol,total flavonoid and seven constituents,respectively,after which the scavenging capacities,reducing powers on DPPH·free radical,ABTS+free radical,hydroxyl free radical,and inhibition capacity on α-glucosidase activity were detected.Subsequently,correlation analysis was performed.RESULTS Total sugar,total protein,total phenol and total flavonoid contents demonstrated significant differences among different dosage forms(P＜0.05,P＜0.01).Calycosin-7-O-β-D-glucoside,glycyrrhizin,codonoside and quercetin displayed the highest contents in the decoction,while those of isoferulic acid,hesperidin and glycyrrhizin were observable in the mixture.The water pill exhibited the strongest antioxidant activity,while those of the concentrated pill and mixture were weak;the big honey pill exhibited the strongest hypoglycemic activity,while that of the decoction was the weakest.Total protein,total phenol,total flavonoid and liquiritin contents displayed significant positive correlations between antioxidant activity(P＜0.05,P＜0.01),while hesperidin content displayed significant negative correlation between the latter(P＜0.05);total protein,calycosin-7-O-β-D-glucoside,codonoside and quercetin contents displayed significant negative correlations between hypoglycemic activity(P＜0.05,P＜0.01).CONCLUSION Active constituent contents and their biological activities of Buzhong Yiqi Recipe with different dosage forms exist differences,total sugar,total protein,total flavonoids,calycosin-7-O-β-D-glucoside,licorice glycoside,hesperidin,codonoside and quercetin can be taken as quality control indices for this prescription.

AIM To compare total sugar,total protein,total phenol,total flavonoid,calycosin-7-O-β-D-glucoside,liquiritin,lobetyolin,quercetin,isoferulic acid,hesperidin,glycyrrhizic acid contents and their antioxidant activities,hypoglycemic activities of big honey pill,small honey pill,water pill,concentrated pill,granule,mixture and decoction of Buzhong Yiqi Recipe.METHODS Anthraquinone-sulfuric acid method,Coomassie brilliant blue method,Folin-phenol colorimetry method,sodium nitrite-aluminum nitrate method and HPLC were adopted in the content determination of total sugar,total protein,total phenol,total flavonoid and seven constituents,respectively,after which the scavenging capacities,reducing powers on DPPH·free radical,ABTS+free radical,hydroxyl free radical,and inhibition capacity on α-glucosidase activity were detected.Subsequently,correlation analysis was performed.RESULTS Total sugar,total protein,total phenol and total flavonoid contents demonstrated significant differences among different dosage forms(P＜0.05,P＜0.01).Calycosin-7-O-β-D-glucoside,glycyrrhizin,codonoside and quercetin displayed the highest contents in the decoction,while those of isoferulic acid,hesperidin and glycyrrhizin were observable in the mixture.The water pill exhibited the strongest antioxidant activity,while those of the concentrated pill and mixture were weak;the big honey pill exhibited the strongest hypoglycemic activity,while that of the decoction was the weakest.Total protein,total phenol,total flavonoid and liquiritin contents displayed significant positive correlations between antioxidant activity(P＜0.05,P＜0.01),while hesperidin content displayed significant negative correlation between the latter(P＜0.05);total protein,calycosin-7-O-β-D-glucoside,codonoside and quercetin contents displayed significant negative correlations between hypoglycemic activity(P＜0.05,P＜0.01).CONCLUSION Active constituent contents and their biological activities of Buzhong Yiqi Recipe with different dosage forms exist differences,total sugar,total protein,total flavonoids,calycosin-7-O-β-D-glucoside,licorice glycoside,hesperidin,codonoside and quercetin can be taken as quality control indices for this prescription.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

AIM:To observe the effect of opioid-free anesthesia with esketamine on delirium after hip replacement surgery in elderly patients.METH-ODS:One hundred and fourteen elderly patients who underwent hip replacement were randomly di-vided into two groups:opioid-free anesthesia(OFA)group and opioid anesthesia(OA)group(n=57).During anesthesia induction and maintenance,es-ketamine was administered in OFA group,and that fentanyl and remifentanil were administered in OA group.Delirium was mainly recorded within 3 days after the surgeries,and the patients'delirium sta-tus was evaluated using the Chinese Revised Deliri-um Diagnostic Scale(CAM-CR).RESULTS:The pa-tients in OFA group had lower CAM-CR scores and delirium incidence compared to those in the OA group at 2 days after surgery.CONCLUSION:Opioid-free anesthesia based on esketamine can effective-ly reduce delirium after hip replacement in elderly patients.

Pulpotomy, which belongs to vital pulp therapy, has become a strategy for managing pulpitis in recent decades. This minimally invasive treatment reflects the recognition of preserving healthy dental pulp and optimizing long-term patient-centered outcomes. Pulpotomy is categorized into partial pulpotomy (PP), the removal of a partial segment of the coronal pulp tissue, and full pulpotomy (FP), the removal of whole coronal pulp, which is followed by applying the biomaterials onto the remaining pulp tissue and ultimately restoring the tooth. Procedural decisions for the amount of pulp tissue removal or retention depend on the diagnostic of pulp vitality, the overall treatment plan, the patient's general health status, and pulp inflammation reassessment during operation. This statement represents the consensus of an expert committee convened by the Society of Cariology and Endodontics, Chinese Stomatological Association. It addresses the current evidence to support the application of pulpotomy as a potential alternative to root canal treatment (RCT) on mature permanent teeth with pulpitis from a biological basis, the development of capping biomaterial, and the diagnostic considerations to evidence-based medicine. This expert statement intends to provide a clinical protocol of pulpotomy, which facilitates practitioners in choosing the optimal procedure and increasing their confidence in this rapidly evolving field.
Humans ; Calcium Compounds/therapeutic use* ; Consensus ; Dental Pulp ; Dentition, Permanent ; Oxides/therapeutic use* ; Pulpitis/therapy* ; Pulpotomy/standards*