OBJECTIVE: To analyze the distribution characteristics of glucose-6-phosphate-dehydrogenase (G6PD) mutations and their enzyme activity in newborns patients with G6PD deficiency in Guilin region. METHODS: From July 2022 to July 2024, umbilical cord blood samples from 4 554 newborns in Guilin were analyzed for G6PD mutations using fluorescence PCR melting curve analysis. Enzyme activity was detected in 4 467 cases using the rate assay. RESULTS: Among 4 467 newborns who underwent G6PD activity testing, 162 newborns (3.63%) were identified as G6PD-deficient, including 142 males (6.04%) and 20 females (0.94%), the prevalence of G6PD deficiency was significantly higher in males than in females (P < 0.001). Genetic analysis of 4 554 newborns detected G6PD mutations in 410 cases (9%), including 171 males (7.13%) and 239 females (11.09%), with a significantly higher mutation detection rate in females than in males (P < 0.001). A total of nine single mutations and four compound heterozygous mutations were identified. The most common mutations were c.1388G>A (33.66%), c.1376G>T (23.66%) and c.95A>G (16.34%). Among newborns who underwent both enzyme activity and genetic mutation testing, males with G6PD mutations had significantly lower enzyme activity than that of females with G6PD mutations(P < 0.001). Specifically, among newborns carrying the mutations c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T or c.871G>A, males consistently exhibited lower enzymatic activity than females with the same mutations (P < 0.001). Furthermore, in male G6PD-deficient newborns, the enzyme activity levels in those carrying c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T, or c.871G>A were lower than those in both the control group and the c.519C>T group (P < 0.05). CONCLUSION This study provides a comprehensive profile of G6PD deficiency incidence and mutation spectrum in the Guilin region. By analyzing enzyme activity and genetic mutation results, this study provides insights into potential intervention strategies and personalized management approaches for the prevention and treatment of neonatal G6PD deficiency in the region.
Humans ; Infant, Newborn ; Glucosephosphate Dehydrogenase Deficiency/epidemiology* ; Glucosephosphate Dehydrogenase/genetics* ; Female ; Male ; Mutation ; China/epidemiology*

To achieve rapid and visual detection of Plasmodium vivax,a detection method based on recombinase polymerase amplification(RPA)technology and lateral flow dipstick(LFD)was established and evaluated.Targeting the conserved sequence of the P.vivax 18S rRNA gene(GenBank:DQ660817.1)as the target sequence,primers and probes were designed with Primer Premier 5,and the P.vivax recombinant plasmid(pUCPv)was constructed as the standard.A sensitive and specific RPA-LFD-based rapid visual detection method for P.vivax nucleic acids was established.The plasmid standard was serially diluted 10-fold to concentrations of 1×103,1×102,1×101,1×10?,and 1×10?1 copies/μL for sensitivity testing.To evaluate specificity,whole blood DNA samples from patients infected with Plasmodium falciparum,Plasmodium malariae,Plasmodium ovale,or Leishmania donovani,as well as healthy participants,were tested by RPA-LFD.Additionally,The assay′s accuracy was evaluated by testing whole blood DNA samples from 24 confirmed P.vivax-infected patients.This study successfully established a sensitive,specific,and rapid visual RPA-LFD method for detecting P.vivax nucleic acids.The assay can complete P.vivax detection within 20 minutes under isothermal conditions at 39 ℃,achieving a sensitivity of 1 copy/μL.There is no significant cross reaction with parasites such as other Plasmodium species and L.donovani,and the specificity is 100%.All 24 DNA samples from confirmed P.vivax patients were detected,showing a 100%detection rate.The developed RPA-LFD assay exhibits excellent sensitivity and specificity,requires only simple heating equipment,and is user-friendly.This rapid visual detection method is particularly suitable for P.vivax screening in low-resource settings.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Objective:To observe the effects of ear acupressure combined with acupoint application on serum inflammatory factors,pain and psychological status of children with limb fractures.Methods:By using random number table method,60 children with limb fracture who were admitted to Qiantang Campus of Zhejiang Provincial Traditional Chinese Medicine Hospital from February 2022 to August 2024 were divided into control group(received conventional treatment combined with acupoint application)and experimental group(combined with ear acupressure based on the control group),with 30 cases in each group.Pain and swelling degree of the affected limb,anxiety and depression[Screening Checklist for Childhood Anxiety Disorders(SCARED),Depression self-rating scale for children(DSRSC)],inflammatory factors[High sensitivity C-reactive protein(hs-CRP),tumor necrosis factor-α(TNF-α),interleukin-6(IL-6),interleukin-1(IL-1)]and family satisfaction rate were compared between the two groups.Results:The scores of visual analogue scale(VAS),SCARED and DSRSC in the experimental group were lower than those in the control group at 1 week and 4 weeks after treatment(P＜0.05).Swelling degree of the affected limb in the experimental group was better than that in the control group at 4 weeks after treatment(P＜0.05).hs-CRP,IL-1,IL-6 and TNF-α in the experimental group were lower than those in the control group at 4 weeks after treatment(P＜0.05).The family satisfaction rate in the experimental group was higher than that in the control group(P＜0.05).Conclusion:Ear acupressure combined with acupoint application therapy for children with limb fractures can significantly alleviate postoperative pain,promote swelling reduction,effectively reduce inflammation,and improve anxiety and depression,with high treatment satisfaction.

AIM To evaluate the quality of benchmark sample of Zexie Decoction.METHODS HPLC fingerprints were established,after which the content determination of epoxy alisma ene,23-acetyl alisol B,23-acetyl alisol C,alisol A,alisol B,atractylenolide Ⅰ,atractylenolide Ⅱ and atractylenolide Ⅲ was performed,and the transfer rate and paste yield were calculated.RESULTS There were 20 common peaks in the fingerprints for 15 batches of benchmark samples with the similarities of more than 0.95.The average contents of various effective constituents were 180.86 μg/g for alisol B 23-acetate,18.65 μg/g for alisol C 23-acetate,34.74 μg/g for alismoxide,17.65 μg/g for alisol A,238.19 μg/g for alisol B,2.85 μg/g for atractylenolide Ⅰ,6.38 μg/g for atractylenolide Ⅱ,and 15.42 μg/g for atractylenolide Ⅲ,respectively.In the decoction piece-benchmark sample,alisol B 23-acetate,alisol C 23-acetate,atractylenolide Ⅰ,atractylenolide Ⅱ and atractylenolide Ⅲ demonstrated the average transfer rates of 12.09％,16.45％,3.93％,12.17％and 34.37％respectively.The paste yields in various batches of benchmark samples were 15.2％-20.2％.CONCLUSION HPLC fingerprints combined with content determination can be used for the quality control of benchmark sample of Zexie Decoction,thus provides a reference for the development of its compound preparations.

AIM To investigate the effects of Qifu Yixin Granules on cardiac inflammation in a rat model of heart failure.METHODS The rats were induced into chronic heart failure(CHF)models by 6-week intraperitoneal injection of doxorubicin followed by the random assignment of the successful rat models into the model group,the captopril group(22.5 mg/kg),and the low-dose,medium-dose,and high-dose Qifu Yixin Granules groups(2.84,5.67,11.34 g/kg),in contrast to the normal rats of the blank group.The rats had their body weight monitored;their cardiac function assessed by echocardiography;their serum levels of NT-proBNP,TNF-α,IL-6,IL-1 and CRP measured by ELISA;their cardiac morphological alterations observed by HE and Masson staining;their cardiac protein expressions of TLR4,MyD88 and NF-κB detected by immunohistochemistry and Western blot;and their cardiac mRNA expressions of TLR4,MyD88 and NF-κB measured by RT-qPCR.RESULTS Compared to the blank group,the model group exhibited significantly reduced body weight,LVEF and LVFS(P＜0.01),alongside significantly elevated LVEDD,LVESD,and serum concentrations of NT-proBNP,TNF-α,IL-6,IL-1 and CRP(P＜0.01).Additionally,the model group displayed greater myocardial inflammatory cell aggregation,increased collagen deposition(P＜0.01);and upregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.01).Compared to the model group,the groups intervened with captopril or medium/high dose Qifu Yixin Granules demonstrated significantly increased body weight,LVEF and LVFS(P＜0.05,P＜0.01);significantly reduced LVEDD,LVESD,and serum levels of the aforementioned indicators(P＜0.05,P＜0.01);mitigated inflammation and collagen deposition(P＜0.05,P＜0.01);and downregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.05,P＜0.01).CONCLUSION Qifu Yixin Granules attenuate cardiac inflammation and improve cardiac function in doxorubicin-induced CHF rats;this therapeutic effect is mediated by inhibiting the activation of the TLR4/MyD88/NF-κB signaling pathway.

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.

ObjectiveAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties with communication and social interaction, restricted and repetitive behaviors. Previous studies have indicated that individuals with ASD exhibit early and lifelong attention deficits, which are closely related to the core symptoms of ASD. Basic visual attention processes may provide a critical foundation for their social communication and interaction abilities. Therefore, this study explores the behavior of children with ASD in capturing attention to changes in topological properties. MethodsOur study recruited twenty-seven ASD children diagnosed by professional clinicians according to DSM-5 and twenty-eight typically developing (TD) age-matched controls. In an attention capture task, we recorded the saccadic behaviors of children with ASD and TD in response to topological change (TC) and non-topological change (nTC) stimuli. Saccadic reaction time (SRT), visual search time (VS), and first fixation dwell time (FFDT) were used as indicators of attentional bias. Pearson correlation tests between the clinical assessment scales and attentional bias were conducted. ResultsThis study found that TD children had significantly faster SRT (P<0.05) and VS (P<0.05) for the TC stimuli compared to the nTC stimuli, while the children with ASD did not exhibit significant differences in either measure (P>0.05). Additionally, ASD children demonstrated significantly less attention towards the TC targets (measured by FFDT), in comparison to TD children (P<0.05). Furthermore, ASD children exhibited a significant negative linear correlation between their attentional bias (measured by VS) and their scores on the compulsive subscale (P<0.05). ConclusionThe results suggest that children with ASD have difficulty shifting their attention to objects with topological changes during change detection. This atypical attention may affect the child’s cognitive and behavioral development, thereby impacting their social communication and interaction. In sum, our findings indicate that difficulties in attentional capture by TC may be a key feature of ASD.

Objective To investigate the neuroprotective effect of rhein(RHE)on ischemic mice and its potential mechanism of reducing inflammatory response and neuronal apoptosis by inhibiting Notch/nuclear factor(NF)-κB signaling pathway.Methods The classical middle cerebral artery occlusion(MCAO)method was used to construct ischemic stroke mouse models.The mice were randomly divided into 5 groups including the sham operation group(sham),the model group(MCAO),the MCAO+edaravone group(Eda),the MCAO+RHE-treated group(RHE),and the MCAO+RHE+Notch activitor Jagged 1 group(RHE+J).Each group has 18 mice.The Bederson scoring system,balance beam walking test and accelerated rotating rod test were used to assess the neurological function and locomotor ability of mice in each group.2,3,5-triphenyltetrazolium chloride(TTC)staining,hematoxylin eosin staining,and TUNEL method were used to assess cerebral infarction,hippocampal morphological damage,and neuronal apoptosis.ELISA was used to analysis the levels of interleukin(IL)-6 and tumor necrosis factor α(TNF-α)in hippocampal tissue.Western blotting was used to analysis caspase-3,Notch 1,Hes1,and NF-κB p65 protein expression.Results Compared with the sham group,Bederson score,balance beam score,cerebral infarct volume,IL-6 and TNF-α levels,the proportion of TUNEL-positively stained cells,caspase-3,Notch1,Hes1,and p-NF-κB p65 protein expression were significantly increased in the MCAO group,whereas the latency to fall decreased significantly(P＜0.05).Compared with the MCAO group,Bederson score,balance beam score,cerebral infarct volume,IL-6 and TNF-α levels,proportion of TUNEL-positively stained cells,caspase-3,Notch1,Hes1,and p-NF-κB p65 protein expression were significantly lower in both Eda and RHE groups,whereas the latency to fall increased significantly(P＜0.05).Compared with the RHE group,Bederson score,balance beam score,cerebral infarction volume,IL-6 and TNF-α levels,the proportion of TUNEL-positively stained cells,caspase-3,Notch1,Hes1,and p-NF-κB p65 protein expression increased significantly in the RHE+J group,whereas the latency to fall decreased significantly(P＜0.05).Conclusion Rhein can significantly improve nerve function in ischemic mice by inhibiting Notch/NF-κB signaling pathway activation,suggesting that rhein has potential clinical application value.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]