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 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 This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Objective:To develop an economical,simple,and accessible method for early identification of high-risk pregnant women with gestational diabetes mellitus(GDM),this study developed and evaluated multiple machine learning models,identified the optimal prediction model,and constructed a clinical decision support sys-tem(CDSS)based on this model.Methods:A total of 464 pregnant women who visited the Second Affiliated Hospital of Dalian Medical University from January 1,2023 to December 30,2024 were included,of which 386 were used to establish a prediction model(231 in the training set and 155 in the testing set),and the remaining 78 were used as a validation.Adopting the methods of double-point sequence correlation and chi-square test,four machine learning models were constructed after selecting feature variables:Logistic Regression,Random Forest,Support Vector Machine,and eXtreme Gradient Boosting(XGBoost).Preliminary judgment of the maximum weight mod-el,further comparison of the discriminative ability,calibration ability,and clinical practicality of each model to evalu-ate and select the optimal model,develop its CDSS,and verify the accuracy of the model.Results:①Correlation analysis identified predictors of GDM:age,pre-pregnancy body mass index(BMI),systolic/diastolic blood pres-sure,white blood cell count,hemoglobin,lymphocyte ratio,fasting plasma glucose,uric acid,direct bilirubin,chronic hypertension complicating pregnancy,and assisted reproductive technology conception.②XGBoost dominated the ensemble model and demonstrated the best performance in discrimination(AUC 0.931,95%CI 0.910-0.967),cali-bration,and clinical utility among the four models.③The CDSS achieved an accuracy of 78.2%,sensitivity of 64.7%,and specificity of 82.0%in the XGBoost model.Conclusions:The XGBoost model has the highest ability to predict GDM in the early stage.Developing its CDSS not only facilitates doctors to quickly assess GDM risk,but also is suitable for promotion to remote areas,where high-risk population screening can be achieved through re-mote data.

Objective To analyze the medication rules and clinical experience of Qin Zujie in treating virtual labor based on data mining.Methods Outpatient medical records of Qin Zujie,diagnosed with deficiency syndrome at Ethnic Medicine Characteristic Diagnosis and Treatment Center,Guangxi International Zhuang Medical Hospital from January to December 2024 were selected.A standardized database was established and processed,yielding 148 clinical prescriptions containing 171 herbal ingredients.Frequency analysis,association rule analysis,and cluster analysis were employed to examine medication rules and clinical experience.Results The 20 Chinese herbal ingredients used more than 30 times each,with the first three being Zhigancao,Baizhu,Danggui.These herbs are primarily warm in nature,neutral in temperature,and slightly cold in effect,characterized by sweet,pungent,and bitter flavors.They mainly affect the spleen meridian and function to tonify deficiency,with Qi-tonifying herbs being the most common.Through association rule analysis,the most frequently combined pairs were Baizhu-Dangshen.Cluster analysis identified three core prescription clusters.Conclusion Qin Zujie's academic thought of treating virtual labor is to supplement deficiency as the main,detoxification as the auxiliary,and treat both the symptoms and the causes.

Objective To evaluate and summarise the best evidence on non-pharmacological preventive measures for lower limb lymphedema in patients with gynecologic malignancy so as to provide an evidence-based guidance for prevention of lower limb lymphedema.Methods Systematic searches were conducted from inception to 31th January,2024 on databases of UpToDate,BMJ Best Practice,the National Institute for Health and Care Excellence(NICE),the Oncology Nursing Society(ONS),Guidelines International Network(GIN),China Guideline Clearinghouse,Medlive,National Comprehensive Cancer Network(NCCN),Registered Nurses Association of Ontario(RNAO),American Society of Clinical Oncology(ASCO),European Society for Medical Oncology(ESMO),Cancer Australia(CA),National Lymphedema Network(NLN),Scottish Intercollegiate Guidelines Network(SIGN),Lymphedema Support Network(LSN),International Society of Lymphology(ISL),International Society of Nurses in Cancer Care,Lymphedema Association of Ontario,Lymphoedema United,Cochrane Library,Web of Science,PubMed,Scopus,OVID,Embase,CINAHL,VIP,Wangfang Data,CNKI and SinoMed for the relevant evidence in non-pharmacological preventive measures for lower limb lymphedema in patients with gynecological malignancy.Two researchers evaluated the quality of clinical decisions,expert consensus,systematic reviews and randomised controlled trials,while four investigators assessed the quality of the guidelines.Another two researchers performed data extraction and evidence summary.Results A total of 17 articles were included,comprising two clinical decisions,two guidelines,two systematic reviews,seven expert consensuses,one evidence summary,three randomised controlled trials.A total of 32 pieces of evidence were summarised across eight dimensions:prevention timing,evaluation element,general self-care,skin care,manual lymphatic drainage,compression therapy,exercise and health education.Conclusion This study provides an evidence-based guidance for prevention of lower limb lymphedema in patients with gynecological malignancy.Healthcare professionals should apply the best evidences based on the conditions,preferences,resource allocation,and other factors of the patients,to reduce limb lymphedema and improve the quality of life of the patients.

Objective To evaluate and summarise the best evidence on non-pharmacological preventive measures for lower limb lymphedema in patients with gynecologic malignancy so as to provide an evidence-based guidance for prevention of lower limb lymphedema.Methods Systematic searches were conducted from inception to 31th January,2024 on databases of UpToDate,BMJ Best Practice,the National Institute for Health and Care Excellence(NICE),the Oncology Nursing Society(ONS),Guidelines International Network(GIN),China Guideline Clearinghouse,Medlive,National Comprehensive Cancer Network(NCCN),Registered Nurses Association of Ontario(RNAO),American Society of Clinical Oncology(ASCO),European Society for Medical Oncology(ESMO),Cancer Australia(CA),National Lymphedema Network(NLN),Scottish Intercollegiate Guidelines Network(SIGN),Lymphedema Support Network(LSN),International Society of Lymphology(ISL),International Society of Nurses in Cancer Care,Lymphedema Association of Ontario,Lymphoedema United,Cochrane Library,Web of Science,PubMed,Scopus,OVID,Embase,CINAHL,VIP,Wangfang Data,CNKI and SinoMed for the relevant evidence in non-pharmacological preventive measures for lower limb lymphedema in patients with gynecological malignancy.Two researchers evaluated the quality of clinical decisions,expert consensus,systematic reviews and randomised controlled trials,while four investigators assessed the quality of the guidelines.Another two researchers performed data extraction and evidence summary.Results A total of 17 articles were included,comprising two clinical decisions,two guidelines,two systematic reviews,seven expert consensuses,one evidence summary,three randomised controlled trials.A total of 32 pieces of evidence were summarised across eight dimensions:prevention timing,evaluation element,general self-care,skin care,manual lymphatic drainage,compression therapy,exercise and health education.Conclusion This study provides an evidence-based guidance for prevention of lower limb lymphedema in patients with gynecological malignancy.Healthcare professionals should apply the best evidences based on the conditions,preferences,resource allocation,and other factors of the patients,to reduce limb lymphedema and improve the quality of life of the patients.

Aim To explore the effects of high glucose on KIAA0753 and CCSAP and the relationship between KIAA0753 and CCSAP and osteogenic differentiation and calcium signaling pathway under high glucose con-ditions.Methods Mouse embryonic osteoblast pre-cursor cells(MC3T3-E1)were induced by osteoblast medium with glucose concentrations of 5.5 and 25 mmol·L-1,and the protein expressions of KIAA0753 and CCSAP were detected by Western blot.The over-expressed plasmid was transfected into human embry-onic kidney cells(HEK-293T),and the interaction between KIAA0753 and CCSAP was detected by co-im-munoprecipitation.MC3T3-E1 cells were treated in the osteogenic medium with different glucose concentrations and induction times.Alkaline phosphatase(ALP)ac-tivity was detected with a kit.The expression of KI-AA0753,CCSAP,osteopontin,osteocalcin,and other proteins were assessed using Western blot.and then 5.5,25 mmol·L-1,and 25 mmol·L-1+OE-CCSAP three groups of MC3T3-E1 cells were set.The expression of KIAA0753,OCN,OPN protein,and ALP activity were detected successively.The diabetic mouse model dataset in Gene Expression Omnibus was used to screen differential genes for bioinformatics a-nalysis.MC3T3-E1 cells were set up in three groups,5.5,25 mmol·L-1,and 25 mmol·L-1+OE-KI-AA0753,respectively.The calcium/calmodulin-de-pendent protein kinase Ⅱ beta(CAMK2B)and phos-pholamban(PLN)were detected by Western blot.Re-sults Compared with the 5.5 mmol·L-1 group,25 mmol·L-1 inhibited the expression of KIAA0753 and CCSAP proteins in osteoblasts,and there was an inter-action between KIAA0753 and CCSAP.At the same time,25 mmol·L-1 also inhibited the expression of ALP,OPN,and OCN proteins in osteoblasts.Overex-pression of CCSAP at 25 mmol·L-1 up-regulated the expression of KIAA0753,OCN,OPN,and ALP.The differential genes of the diabetic mouse model were mainly concentrated in the aspects of"signal receptor and signal regulation".25 mmol·L-1 glucose inhibi-ted the expression of CAMK2B and PLN proteins in os-teoblasts,and overexpression of KIAA0753 at 25 mmol·L-1 upregulated the expression of CAMK2B and PLN proteins.Conclusions High glucose inhibits the expression of KIAA0753 and CCSAP protein,inhibits the osteogenic differentiation and calcium signaling in mouse embryonic osteoblast precursor cells,overex-pression of CCSAP saves the inhibitory effect of high glucose on osteogenic differentiation,and overexpres-sion of KIAA0753 reverses the inhibitory effect of high glucose on calcium signaling pathway.

Objective:To develop an economical,simple,and accessible method for early identification of high-risk pregnant women with gestational diabetes mellitus(GDM),this study developed and evaluated multiple machine learning models,identified the optimal prediction model,and constructed a clinical decision support sys-tem(CDSS)based on this model.Methods:A total of 464 pregnant women who visited the Second Affiliated Hospital of Dalian Medical University from January 1,2023 to December 30,2024 were included,of which 386 were used to establish a prediction model(231 in the training set and 155 in the testing set),and the remaining 78 were used as a validation.Adopting the methods of double-point sequence correlation and chi-square test,four machine learning models were constructed after selecting feature variables:Logistic Regression,Random Forest,Support Vector Machine,and eXtreme Gradient Boosting(XGBoost).Preliminary judgment of the maximum weight mod-el,further comparison of the discriminative ability,calibration ability,and clinical practicality of each model to evalu-ate and select the optimal model,develop its CDSS,and verify the accuracy of the model.Results:①Correlation analysis identified predictors of GDM:age,pre-pregnancy body mass index(BMI),systolic/diastolic blood pres-sure,white blood cell count,hemoglobin,lymphocyte ratio,fasting plasma glucose,uric acid,direct bilirubin,chronic hypertension complicating pregnancy,and assisted reproductive technology conception.②XGBoost dominated the ensemble model and demonstrated the best performance in discrimination(AUC 0.931,95%CI 0.910-0.967),cali-bration,and clinical utility among the four models.③The CDSS achieved an accuracy of 78.2%,sensitivity of 64.7%,and specificity of 82.0%in the XGBoost model.Conclusions:The XGBoost model has the highest ability to predict GDM in the early stage.Developing its CDSS not only facilitates doctors to quickly assess GDM risk,but also is suitable for promotion to remote areas,where high-risk population screening can be achieved through re-mote data.

Combined small cell lung cancer(C-SCLC)accounts for approximately 20%of all SCLC cases,while the propotion of C-SCLC mixed with squamous cell carcinoma component comprises less than 3%.At the pathological level,accurate diagnosis requires to distinguish it from other lung tumor types,and even rely on molecular testing.This article presents a case of a 67-year-old patient initially diagnosed with a peripheral lung tumor.The patient underwent comprehensive multidisciplinary management,including surgical resection,postoperative pathological differential diagnosis,chemotherapy,thoracic radiotherapy,brain metastasis,cranial radiotherapy,dynamic follow-up of imaging changes after cranial radiotherapy,and cranial surgery.Molecular residual disease(MRD)monitoring was integrated at critical time points during dynamic monitoring to inform personalized treatment decisions.The early MDT has brought the patient′s condition under control,and the overall survival of the patient exceeded 30 months.Through the introduction of the diagnosis and treatment process of this patient,we aim to offer novel perspectives on clinical decision-making for C-SCLC.