ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

Objective To understand the antibody levels of diphtheria and tetanus among healthy population in Shanghai Pudong New Area, and to provide a scientific basis for improving the vaccine immunization strategy. Methods Random sampling was used to select healthy people of all ages in 16 communities in Shanghai Pudong New Area from 2018 to 2024, and serum samples were collected and tested for serum anti-diphtheria and tetanus toxin IgG antibodies by enzyme-linked immunosorbent assay (ELISA) method to analyze the antibody positivity rate (≥0.1 IU/ml) and the geometric mean concentration (GMC) of antibodies. Results A total of 3 312 serum samples were included, with a male-to-female ratio of 0.76:1, and 53.77% were local residents. The seropositivity rates and geometric mean concentrations (GMC) of both diphtheria and tetanus antibodies generally declined with increasing age, but exhibited a transient rebound in the 7y-. A total of 1 175 individuals (35.48%) were seropositive for diphtheria, with a GMC of 0.054 IU/mL. For tetanus, 988 individuals (29.83%) were seropositive, with a GMC of 0.033 IU/mL. Significant differences in seropositivity rates (χ²_diphtheria=950.005,χ²_tetanus=1 324.393) and GMC (H_diphtheria=1027.160,H_tetanus=1 142.007) were observed among different age groups (P<0.001). Significant differences in seropositivity rates (χ²_diphtheria=950.005,χ²_tetanus=1324.393) and GMC (H_diphtheria=1027.160,H_tetanus=1142.007) were also found across different years (P<0.001). Conclusion The prevalence of diphtheria and tetanus antibodies in the healthy population of Pudong New Area is relatively low, particularly among adults over 20 years of age with inadequate immunization. This underscores the need to reinforce the National Immunization Program (NIP) vaccine specifications for children under 6 years of age and implement an immunization strategy for adolescents or adults against diphtheria and tetanus.

Objective To construt and validate a risk prediction model for hepatocellular carcinoma(HCC)in patients with chronic liver disease based on age-male-ALBI-platelets(aMAP)score combined with RAR and PIV.Methods A total of 143 patients with chronic liver disease were divided into the HCC group(32 cases)and the non-HCC group(111 cases)according to whether HCC occurred.General clinical data,aMAP score and peripheral blood indicator level were compared between two groups.Multivariate Logistic regression was used to analyze influencing factors of HCC in inpatients with chronic liver disease.A nomogram risk prediction model was constructed and validated.Results Compared with the non-HCC group,there were higher age,higher proportion of males,higher levels of total bilirubin(TBIL),red blood cell distribution width(RDW),neutrophil count(NEU)and monocyte count(MON),lower levels of albumin(ALB)and lymphocyte count(LYM),higher levels of aMAP score,RDW to ALB(RAR)and pan-immune inflammation value(PIV)in the HCC group(P＜0.05).Multivariate Logistic regression showed that higher levels of aMAP score,RAR and PIV were independent risk factors for HCC in inpatients with chronic liver disease(P＜0.05).The area under receiver operator characteristic(ROC)curve(AUC)of the nomogram risk prediction model constructed based on above factors was 0.823(95%CI:0.747-0.899).The calibration curve showed that the predicted value was basically consistent with the actual observed value,and the Brier score was 0.125.The decision curve showed that the model had a clear positive net benefit.The AUC of internal validation of the prediction model by Bootstrap method was 0.823(95%CI:0.820-0.825),indicating that the model had a good degree of differentiation.Conclusion The nomogram risk prediction model based on aMAP score,RAR and PIV showed a good predictive performance of HCC in patients with chronic liver disease,which could benefits the individualized treatment and follow-up.

Objective:To explore the factors influencing the non-reversal of mild cognitive impairment (MCI) after a first stroke.Methods:A total of 243 first stroke patients with MCI were enrolled at the First Affiliated Hospital of Zhengzhou University from March 2020 to March 2023. The patients were followed up for one year to assess the reversal of MCI. Patients who did not undergo reversal and those who did undergo reversal were included in non-reversal group and reversal group, respectively. General information of non-reversal group and reversal group was compared. Binary Logistic regression was used to analyze the factors influencing the non-reversal of MCI after a first stroke.Results:After one year of follow-up, the non-reversal rate was 25.10% (61/243) among 243 first stroke patients with MCI. Binary Logistic regression analysis showed that older age, history of diabetes, high National Institute of Health Stroke Scale (NIHSS) score at admission, left-sided lesions, and modified Fazekas grade 3 were risk factors for non-reversal of MCI after a first stroke ( P<0.05), while educational level of college degree or above was a protective factor ( P<0.05) . Conclusions:Older age, history of diabetes, high NIHSS score at admission, left-sided lesions, and modified Fazekas grade 3 are risk factors for non-reversal of MCI after a first stroke, while an educational level of college degree or above is a protective factor.

Extended reality(XR)technology includes virtual reality(VR),augmented reality(AR)and mixed reality(MR)Combining virtual environments with physical world,the extended reality(XR)technology has great potential in rehabilitation of patients with stroke.This article reviews the intervention effects of XR technology on the functions of limb,swallowing,speech and cognition and psychological outcomes in patients with stroke.Based on this review,issues in application of XR are identified and targeted solutions are proposed,thereby offering a guidance for application of XR technology in stroke rehabilitation in China.

Extended reality(XR)technology includes virtual reality(VR),augmented reality(AR)and mixed reality(MR)Combining virtual environments with physical world,the extended reality(XR)technology has great potential in rehabilitation of patients with stroke.This article reviews the intervention effects of XR technology on the functions of limb,swallowing,speech and cognition and psychological outcomes in patients with stroke.Based on this review,issues in application of XR are identified and targeted solutions are proposed,thereby offering a guidance for application of XR technology in stroke rehabilitation in China.

Objective: This study aims to elucidate the role of aryl hydrocarbon receptor nuclear transporter 2 (ARNT2) in cervical cancer (CC) and explore the potential mechanism by which ARNT2 promotes the progression of CC through the protein phosphatase 2A (PP2A)/Akt signaling pathway. Methods: Bioinformatics tools were used to analyze the expression level of ARNT2 in cancer and its correlation with cancer prognosis. Western Blot and immunohistochemistry staining were used to detect the expression of ARNT2 protein in CC tissues and cells. ARNT2 was knocked down in SiHa and HeLa cells, respectively. Cell Counting Kit-8 assay and colony formation assay were used to detect changes in cell proliferation. Transwell assay and plate scratch assay were used to detect changes in cell migration and invasion. Western Blot assay was used to detect changes in the expression of PP2A/Akt signaling pathway after ARNT2 expression was downregulated. Finally, a CC xenograft tumor model was constructed to evaluate the effect of ARNT2 on SiHa cell tumorigenesis in vivo. Results: ARNT2 is highly expressed in tumor tissues and cell lines. ARNT2 knockdown can significantly inhibit the proliferation, invasion and migration of SiHa and HeLa cells in vitro and in xenograft models. Further studies have shown that ARNT2 may promote tumor formation by regulating the PP2A/Akt pathway. Conclusion ARNT2 promotes the malignant biological behavior of CC cells through the PP2A/Akt signaling pathway, confirming its potential as a prognostic marker for CC.

Objective:To explore the factors influencing the non-reversal of mild cognitive impairment (MCI) after a first stroke.Methods:A total of 243 first stroke patients with MCI were enrolled at the First Affiliated Hospital of Zhengzhou University from March 2020 to March 2023. The patients were followed up for one year to assess the reversal of MCI. Patients who did not undergo reversal and those who did undergo reversal were included in non-reversal group and reversal group, respectively. General information of non-reversal group and reversal group was compared. Binary Logistic regression was used to analyze the factors influencing the non-reversal of MCI after a first stroke.Results:After one year of follow-up, the non-reversal rate was 25.10% (61/243) among 243 first stroke patients with MCI. Binary Logistic regression analysis showed that older age, history of diabetes, high National Institute of Health Stroke Scale (NIHSS) score at admission, left-sided lesions, and modified Fazekas grade 3 were risk factors for non-reversal of MCI after a first stroke ( P<0.05), while educational level of college degree or above was a protective factor ( P<0.05) . Conclusions:Older age, history of diabetes, high NIHSS score at admission, left-sided lesions, and modified Fazekas grade 3 are risk factors for non-reversal of MCI after a first stroke, while an educational level of college degree or above is a protective factor.

Objective To construt and validate a risk prediction model for hepatocellular carcinoma(HCC)in patients with chronic liver disease based on age-male-ALBI-platelets(aMAP)score combined with RAR and PIV.Methods A total of 143 patients with chronic liver disease were divided into the HCC group(32 cases)and the non-HCC group(111 cases)according to whether HCC occurred.General clinical data,aMAP score and peripheral blood indicator level were compared between two groups.Multivariate Logistic regression was used to analyze influencing factors of HCC in inpatients with chronic liver disease.A nomogram risk prediction model was constructed and validated.Results Compared with the non-HCC group,there were higher age,higher proportion of males,higher levels of total bilirubin(TBIL),red blood cell distribution width(RDW),neutrophil count(NEU)and monocyte count(MON),lower levels of albumin(ALB)and lymphocyte count(LYM),higher levels of aMAP score,RDW to ALB(RAR)and pan-immune inflammation value(PIV)in the HCC group(P＜0.05).Multivariate Logistic regression showed that higher levels of aMAP score,RAR and PIV were independent risk factors for HCC in inpatients with chronic liver disease(P＜0.05).The area under receiver operator characteristic(ROC)curve(AUC)of the nomogram risk prediction model constructed based on above factors was 0.823(95%CI:0.747-0.899).The calibration curve showed that the predicted value was basically consistent with the actual observed value,and the Brier score was 0.125.The decision curve showed that the model had a clear positive net benefit.The AUC of internal validation of the prediction model by Bootstrap method was 0.823(95%CI:0.820-0.825),indicating that the model had a good degree of differentiation.Conclusion The nomogram risk prediction model based on aMAP score,RAR and PIV showed a good predictive performance of HCC in patients with chronic liver disease,which could benefits the individualized treatment and follow-up.