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.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Fire twinkling is the common method in cupping therapy. In the teaching materials of acupuncture and moxibustion, and the national standard, Standardized Manipulations of Acupuncture and Moxibustion-Part 5: Cupping Therapy, this cupping technique is operated by igniting an alcohol-soaked cotton ball held with a forceps, placing it inside the cup, taking it out after "turning around in several circles", and placing the cup on the selected area. Based on the clinical experience of chief physician LI Yan, a high-efficient and safe fire twinkling was developed. Clamping the middle part of the cotton ball with a holder, dipping it in 95% ethanol, and squeezing the cotton ball to ensure no ethanol drops left; holding the cup with the dominant hand and covering the ignited cotton ball vertically, removing the cup immediately when the ball touching the cup bottom. Such manipulation mode, "flame going in and out directly", can avoid the potential safety hazards such as residual ethanol left on the cup opening, overheating of cup opening and accidentally falling-off of the ignited cotton ball.
Humans ; Cupping Therapy/instrumentation* ; Acupuncture Therapy/instrumentation* ; Fires

To explore the understanding of the target population regarding the Get Active Questionnaire for Pregnancy(GAQ-P)and the Companion Health Care Provider Consultation Form for Prenatal Physical Activity(cHCP-CF-PPA)in the Chinese context,and to verify the consistency of the Chinese version of the prenatal physical activity dual screening questionnaire with the original version in terms of language expression,27 pregnant women and 12 healthcare providers were selected from Obstetrics and Gynecology Hospital,Fudan University during Aug and Oct 2023,and were interviewed using purposive sampling.Two rounds of cognitive interviews were conducted.The first round revealed that some respondents experienced ambiguities in understanding the meanings of 5 items in the questionnaire.Following modifications,the second round indicated that the revised items were consistent in meaning with the original questionnaire.Cognitive interviews can facilitate the adaptation of the prenatal physical activity dual screening questionnaire to the Chinese cultural context,improve the understanding of the questionnaire items among the target population,and promote the localization of the screening tool.

In recent years,the prevalence of porcine infectious pleuropneumonia caused by Actinoba-cillus pleuropneumoniae(APP)has significantly increased in large-scale pig farms in China.The i-solation,identification,and biological characteristic testing of newly prevalent strains have impor-tant clinical significance.This study isolated four suspected APP strains(named XB2T-56,JMTLP-443,YD-THB-755,SYZJ-291)from lung samples of pig farms suspected of outbreaks of porcine infectious pleuropneumonia in Hubei Province.They were identified by PCR amplification,and multiplex PCR serological typing,the biological properties were tested by detecting the growth a-bility,hemolytic activity and biofilm forming ability.The drug resistance of the strains was ana-lyzed by drug sensitivity testing,and the virulence of one strain(XB2T-56)in mice and piglets was evaluated.The PCR identification result showed that all four clinical isolates were APP serotype 15 strains.These four strains grew slower than serotype 1 standard strains,had weaker hemolytic activity,but could form stronger biofilms.These strains are all less sensitive to cephalosporin,tylo-sin,sulfamethoxazole,and doxycycline,but sensitive to cefotaxime and enrofloxacin.The mice and piglet infection experiments showed that the isolated strain XB2T-56 has strong virulence.Artifi-cial intranasal infection causes acute death in piglets,with typical symptoms of pleuropneumonia in the lungs,and serotype 15 strains can be isolated from the lesion site.This study indicates that the APP serotype 15 strain has strong virulence,providing new date for the clinical epidemiological characteristics of APP.

Aberrant expression of Colgalt1 is closely associated with tumorigenesis and tumor progres-sion;however,the mechanism by which it regulates macrophages to influence tumor development remains poorly understood.This study aimed to establish a macrophage-specific Colgalt1 gene knockout mouse model to delve into the mechanisms through which Colgalt1 modulates macrophage function and subse-quently affects the occurrence and progression of tumor-related diseases.Initially,Colgalt1flox+mice were generated using gene editing techniques,followed by crossing with Lyz2-Cre+mice,which exhibit tissue-specific expression in the myeloid lineage(including monocytes and mature macrophages).Through this strategy,mice with the genotype Colgalt1-/-Lyz2-Cre+were successfully obtained,achieving conditional knockout of the Colgalt1 gene in macrophages.Colgalt1flox/flox Lyz2-Cre-mice were used as control.PCR and agarose gel electrophoresis were employed to identify the Flox and Cre genotypes of the knockout mice.RT-qPCR and Western Blot techniques were utilized to detect the expression levels of Colgalt1 in BMDMs from knockout mice at both the mRNA and protein levels,respectively.Western Blot results re-vealed a significant downregulation of Colgaltl expression in BMDMs from knockout mice compared to controls(P＜0.01).RT-qPCR results demonstrated a significant reduction in Colgalt1 mRNA levels in BMDMs from knockout mice compared to contro1s(P＜0.001),while no significant differences in Col-galt1 mRNA expression were observed in liver,lung,or spleen tissues between the two groups.Addition-ally,immunohistochemistry was employed to detect Colgalt1 expression in liver-specific macrophages,re-vealing an absence of Colgalt l-positive staining in liver macrophages from knockout mice.HE staining was used to observe cellular morphology in liver tissues from both groups of mice,showing no significant differences in cellular morphology or obvious pathological changes in tissues and organs.Moreover,the o-verall survival of the mice was not affected.Finally,RT-qPCR was used to assess the expression of mac-rophage-related inflammatory factors in BMDMs from both groups of mice.The results indicated that com-pared to controls,knockout mice exhibited downregulated expression of TNF-α(P＜0.05)and signifi-cantly upregulated expression of IL-10(P＜0.01),Arginase1(P＜0.001),and CD206(P＜0.001)in BMDMs,suggesting an anti-inflammatory trend and M2 polarization of macrophages following Colgalt 1 knockout.In summary,this study successfully established a macrophage-specific Colgalt1 gene knockout mouse model,providing a more reliable experimental animal model for in-depth exploration of the specific roles of Colgalt1 in macrophage functional regulation and the pathogenesis of tumor-related diseases.This model holds promise for identifying novel therapeutic targets and strategies for tumors and other diseases.

Objective:To evaluate the application effect of a wearable visual field meter based on extended reality (XR) glasses for patients with macular disease.Methods:A self-controlled study was conducted.A total of 41 consecutive patients (41 eyes) with macular disease were recruited at Renmin Hospital of Wuhan University from October 2022 to October 2024.All patients underwent 10-2 center visual field test using a self-developed wearable visual field meter (XRVF), and the results were compared with those obtained using a traditional Humphrey field analyzer (HFA).The comparison parameters included mean retinal sensitivity (MS), false positive rate (FPR), false negative rate (FNR), and testing duration.A subject satisfaction questionnaire was administered.This study followed the Declaration of Helsinki.The study protocol was approved by the Medical Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY2024-K263), and all subjects signed the informed consent form.Results:The retinal sensitivity of patients measured by HFA was (23.24±3.71)dB, which was higher than (22.01±3.45)dB by XRVF, showing a statistically significant difference ( t=4.924, P=0.036).The FPR measured by HFA and XRVF were (2.39±2.51)% and (2.59±3.29)%, respectively, and the FNR were (3.49±6.05)% and (3.74±5.38)%, respectively, showing no statistically significant difference ( t=-3.624, P=0.948; t=-1.241, P=0.519).The median test duration for HFA and XRVF was 6.15 (5.78, 6.65) and 5.98 (5.71, 6.69)minutes, respectively, without statistically significant difference ( Z=-1.987, P=0.953).92.6% of the subjects thought the device was comfortable, simple and practical. Conclusions:The XRVF has good consistency with the HFA, can effectively and reliably evaluate the visual field function of patients with macular disease, and is easily accepted by patients.

Objective To investigate the dosimetric effect of a biological optimization approach combining physical optimization with generalized equivalent uniform dose(gEUD)on hippocampus avoidance whole-brain radiotherapy(HA-WBRT).Methods A retrospective review was conducted of 20 patients with multiple brain metastases who underwent whole-brain radiotherapy at a certain hospital between May 2021 and December 2022.Two radiotherapy plans including plan_DV and plan_gEUD were designed for each patient by using Eclipse V15.6 planning system.Plan_DB used conven-tional dose-volume(DV)physical optimization,and plan_gEUD went through re-optimization with an Upper gEUD function applied to hippocampal region and hippocampal protection zone.Evaluation was carried out in accordance with RTOG 0933 guidance for the absolute values D2%,D98%and D50%received by 2%,98%,and 50%of the target volume in the planning target volume,conformity index(CI),homogeneity index(HI),gradient index(GI)and the dosimetric indexes of hippocampal region,hippocampal protection zone and other organs at risk(OARs).SPSS 26.0 software was used for statistical analysis.Results The two kinds of plans both had the target volume coverage meet the requirements of RTOG 0933 guidance.Plan_gEUD had the D98%,D2%and V105 of the planning target volume lower than those of plan_DV,with the differences being statistically significant(all P<0.05).The two kinds of plans had no significant differences in monitor unit,D50%and Dmax of PTV,HI,CI and GI(all P>0.05).Plan_gEUD had the Dmax and Dmean of hippocampal region and them of hippocampal pro-tection zone lower than those of plan_DV,and the optic nerve Dmax of plan_gEUD was higher than that of plan_DV,with the differences being statistically significant(all P<0.05).There were no statistically significant differences between the two kinds of plans in the Dmax of inner ear,optic chiasm,lens,and eyeball(all P>0.05).Conclusion Physical optimization in the HA-WBRT plan combined with gEUD optimization results in a greater dose reduction to the hippocampus while maintaining target coverage.

Objective To investigate the dosimetric effect of a biological optimization approach combining physical optimization with generalized equivalent uniform dose(gEUD)on hippocampus avoidance whole-brain radiotherapy(HA-WBRT).Methods A retrospective review was conducted of 20 patients with multiple brain metastases who underwent whole-brain radiotherapy at a certain hospital between May 2021 and December 2022.Two radiotherapy plans including plan_DV and plan_gEUD were designed for each patient by using Eclipse V15.6 planning system.Plan_DB used conven-tional dose-volume(DV)physical optimization,and plan_gEUD went through re-optimization with an Upper gEUD function applied to hippocampal region and hippocampal protection zone.Evaluation was carried out in accordance with RTOG 0933 guidance for the absolute values D2%,D98%and D50%received by 2%,98%,and 50%of the target volume in the planning target volume,conformity index(CI),homogeneity index(HI),gradient index(GI)and the dosimetric indexes of hippocampal region,hippocampal protection zone and other organs at risk(OARs).SPSS 26.0 software was used for statistical analysis.Results The two kinds of plans both had the target volume coverage meet the requirements of RTOG 0933 guidance.Plan_gEUD had the D98%,D2%and V105 of the planning target volume lower than those of plan_DV,with the differences being statistically significant(all P<0.05).The two kinds of plans had no significant differences in monitor unit,D50%and Dmax of PTV,HI,CI and GI(all P>0.05).Plan_gEUD had the Dmax and Dmean of hippocampal region and them of hippocampal pro-tection zone lower than those of plan_DV,and the optic nerve Dmax of plan_gEUD was higher than that of plan_DV,with the differences being statistically significant(all P<0.05).There were no statistically significant differences between the two kinds of plans in the Dmax of inner ear,optic chiasm,lens,and eyeball(all P>0.05).Conclusion Physical optimization in the HA-WBRT plan combined with gEUD optimization results in a greater dose reduction to the hippocampus while maintaining target coverage.