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.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

Objective To analyze the efficacy, safety, and learning curve of the three-lobe holmium laser enucleation of the prostate(HoLEP)in the treatment of benign prostatic hyperplasia(BPH)in a county-level hospital.Methods A retrospective analysis was conducted on the clinical data of 65 BPH patients who underwent the three-lobe HoLEP performed by a single surgeon at the Department of Urology, Yining County People's Hospital, during Dec.2023 and Jun.2024.The enucleation efficiency was calculated by dividing the weight of the enucleated prostatic tissue by the enucleation time.A case scatter diagram of enucleation efficiency was plotted according to the chronological order of the operations, and the learning curve was analyzed after fitting.Based on the inflection points of the learning curve, the learning process was divided into the initial learning, mastery, and proficiency phases.The basic clinical data, perioperative indicators, postoperative complications, and follow-up indicators were compared among the different learning phases.Results All 65 procedures were successfully completed.Marked by the enucleation efficiency reaching a plateau, cases 1-20 were defined as the initial learning phase, cases 21-40 as the mastery phase, and cases 41 onwards as the proficiency phase.The prostate volume in the proficiency phase was significantly larger than that in the initial learning and mastery phases(both P＜0.05).There were no statistically significant differences in other baseline characteristics among the three groups(all P＞0.05).The operation time [(105.50±19.12)min vs.(85.25±26.92)min vs.(69.00±23.58)min] and enucleation time [(76.90±14.19)min vs.(63.70±22.24)min vs.(48.80±20.48)min] showed a decreasing trend across the three groups(all P＜0.05).The enucleation efficiency in both the mastery and proficiency phases was significantly higher than that in the initial learning phase [(1.16±0.44)g/min vs.(0.85 ±0.25)g/min, P＜0.05;(1.36±0.49)g/min vs.(0.85±0.25)g/min, P＜0.05].The enucleation efficiency in the proficiency phase was slightly higher than that in the mastery phase, but the difference was not statistically significant(P= 0.389).There was no significant difference in the incidence of perioperative complications among the three groups(all P＞0.05).At the 6-month follow-up, the international prostate symptom score(IPSS), post-void residual(PVR), and maximum urinary flow(Qmax)were significantly improved compared to preoperative values in all three groups(all P＜0.05);however, no significant differences were observed among the three groups(all P＞0.05).Conclusion The three-lobe HoLEP for the treatment of BPH is safe and effective in a county-level hospital setting.Surgeons with some experience in endoscopic surgery can preliminarily master this technique after a learning period of approximately 20 procedures.

ObjectiveTo investigate the effect of Sanet Vision Integrator (SVI)-based visuomotor integration training on the severity of neglect symptoms, upper limb motor function and activities of daily living (ADL) in patients with post-stroke unilateral spatial neglect (USN). MethodsFrom July, 2023 to September, 2025, 41 patients with post-stroke USN in Beijing Bo'ai Hospital were enrolled and randomly assigned to control group (n = 20) and experimental group (n = 21). Both groups received conventional rehabilitation and visual scanning training, while the experimental group received supplementary SVI-based visuomotor integration training, including saccadic, rotation and hand-eye coordination training, for eight weeks. They were assessed with Chinese Behavioral Inattention Test-Hong Kong version (CBIT-HK), Fugl-Meyer Assessment-Upper Extremities (FMA-UE) and modified Barthel Index (MBI) before and after treatment. ResultsAfter treatment, all the scores significantly improved in both groups (|t| > 4.004, P < 0.001), and the total scores of CBIT-HK and the core visual search sub-items (star cancellation, line crossing and letter cancellation), FMA-UE and MBI were better in the experimental group than in the control group (t > 2.096, P < 0.05). ConclusionSVI-based visuomotor training can effectively alleviate the USN symptoms, broaden the span of visual attention, facilitate the functional recovery of the affected upper extremity, and improve ADL in patients after stroke.

Objective:To investigate the clinical characteristics of limb overgrowth following proximal femoral osteotomy (PFO) for unilateral developmental dysplasia of the hip (DDH) in children.Methods:A retrospective analysis was conducted on 36 children with unilateral DDH who underwent PFO at Xi'an Honghui Hospital from June 2017 to June 2021. The cohort included 4 males and 32 females, with a mean age of 4.23±3.15 years (range: 2-12 years), comprising 28 left-sided and 8 right-sided cases. According to the International Hip Dysplasia Institute (IHDI) classification, there were 2 type I, 9 type II, 16 type III, and 9 type IV cases. Radiographic parameters [femoral length, femoral neck anteversion angle, neck-shaft angle, acetabular index (AI), center-edge angle (CEA), center-head distance discrepancy (CHDD)] and PFO parameters (varus angle, shortening length, derotation angle) were measured on X-ray and 3D CT reconstructions. Comparisons were made between the overgrowth ≥1 cm group ( n=14) and <1 cm group ( n=22) to analyze risk factors and patterns. Results:The overgrowth ≥1 cm group had significantly younger patients (2.49±1.03 years vs. 5.13±3.47 years, t=-2.757, P<0.001). Overgrowth magnitude varied significantly across age subgroups: 11.08±6.17 mm in the 2-4 years group, 5.08±0.19 mm in the >4-<6 years group, and 2.44±4.50 mm in the ≥6 years group ( F=5.436, P=0.031). The highest incidence of overgrowth occurred in the 2-4 years subgroup (56%, 20/36). Limb overgrowth initiated at 3 months postoperatively, exhibited a linear correlation with follow-up duration during 6-18 months [ r=0.78, 95% CI(0.62, 0.88), P<0.001)], and plateaued after 18 months [ r=-0.15, 95% CI(-0.75, 0.57), P=0.710]. Postoperative CEA and CHDD showed significant improvements ( P<0.05), while AI remained unchanged ( P>0.05). Conclusions:Children aged 2-4 years exhibit higher incidence and severity of post-PFO limb overgrowth. The rapid progression phase occurs within 6-18 months postoperatively, stabilizing thereafter. CEA and CHDD serve as critical indicators for evaluating intervention efficacy in DDH-related overgrowth.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

[Objective]To construct a prediction model for brucellosis by using a deep neural network algorithm to improve the early detection.[Methods]We collected the clinical data of 202 brucellosis patients and 319 non-brucellosis patients admitted to Hohhot Occupational Disease Prevention and Treatment Hospital in 2023,and analyzed data such as gender,age,blood routine indices and clinical diagnosis.A prediction model for brucellosis was constructed by using a deep neural network algorithm and optimized through 10-fold cross-validation.Performance metrics included sensitivity,false negative rate,specificity,false positive rate,accuracy,positive predictive value,negative predictive value,F1 score,and area under the receiver operating characteristic curve(AUC).The optimal model was interpreted by using SHapley Additive exPlanations(SHAP)to clarify decision-making logic and feature influencing mechanisms.[Results]Data visualization analysis revealed no significant difference between brucellosis and non-brucellosis groups.The optimal model demonstrated good performance:sensitivity(85.3%),specificity(92.1%),accuracy(89.5%),AUC(96.6%),95%CI(0.937,0.977).SHAP analysis identified age,platelet count,mean platelet volume,basophil ratio,red blood cell distribution width,and absolute basophil count as significant predictors of brucellosis.[Conclusions]The deep neural network prediction model constructed in this study has good performance and can provide reliable support for the early diagnosis,prevention and control of brucellosis.Identification of key brucellosis-related influencing features will help further understand the pathogenesis of the disease,and this model holds promise for broad clinical application in the future.