ObjectiveTo establish a reliable chronic obstructive pulmonary disease (COPD) mouse model based on a self-developed multichannel automatic control system for long-term continuous cigarette smoke exposure in small animals using a novel continuous cigarette smoke exposure method, and to conduct phenotypic evaluation and analysis, thereby providing an animal experimental basis for investigating COPD pathogenesis and prevention strategies. MethodsTwenty male C57BL/6J mice aged 6 weeks were randomly and equally divided into a control group and a model group. The model group (n=10) underwent 6 h of continuous cigarette smoke exposure daily (6 cigarettes per day for 12 consecutive weeks), while the control group (n=10) received no intervention. Body weight was monitored biweekly. Post-exposure, in vivo micro-CT imaging was performed. After euthanasia, serum and bronchoalveolar lavage fluid (BALF) levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) were quantified by ELISA. Lung tissues underwent H&E and Masson's trichrome staining to observe changes in lung morphology and inflammatory cell infiltration, and the mean linear intercept (MLI) was calculated, thereby comprehensively evaluating the clinical features of COPD in the mouse model. ResultsCompared with the control group, the model group showed significantly reduced body weight (P<0.01) from the fourth week. Compared with the control group, IL-6 level in the serum and BALF of the model group increased by 27.2% and 140.0%, respectively (P<0.01). TNF-α level in the serum and bronchoalveolar lavage fluid of the model group increased by 16.7% (P<0.01) and 19.3% (P<0.05), respectively. Histopathological examination revealed alveolar wall thinning, septal rupture, emphysematous bullae formation, reduced alveolar count, bronchial wall thickening with lumen narrowing, and inflammatory cell infiltration. MLI was significantly elevated (P<0.01). Masson's staining confirmed collagen deposition and bronchial remodeling. Micro-CT demonstrated localized high-density shadows exhibiting typical features of chronic bronchitis. Conclusion The self-developed device enables long-term continuous smoke exposure, and the successfully established COPD mouse model exhibits pathological features highly consistent with clinical manifestations, offering an efficient and reliable tool for COPD research.

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.

ObjectiveThe biosynthesis of heterophyllin B （HB）， a cyclopeptide from Pseudostellaria heterophylla， is regulated by various abiotic stresses. Elucidating the transcriptional regulatory mechanism underlying HB biosynthesis is of great guiding significance for the directional improvement of P. heterophylla varieties and the enhancement of HB content. MethodsBased on transcriptome data from different tissues of P. heterophylla， transcription factors （TFs） specifically upregulated and highly expressed in the phloem of tuberous roots were screened through a combination of Mfuzz time-series clustering， transcription factor family prediction， and correlation analysis. Quantitative real-time polymerase chain reaction （Real-time PCR） was employed to analyze expression patterns of candidate TFs under abscisic acid （ABA） induction， and the dual-luciferase reporter assay was applied to verify their regulatory effects on HB precursor genes. ResultsContent determination showed that HB accumulated at the highest in the phloem of P. heterophylla tuberous roots （34 μg·g^-1 fresh weight）. Transcriptome analysis identified 15 868 up-regulated differentially expressed genes （DEGs）， among which 4 375 were specifically up-regulated in the phloem. From these， 25 TFs highly expressed in the phloem were screened. Correlation analysis revealed that the expression level of WRKY70 was significantly positively correlated with HB content， the expression of precursor genes prePhHB， and PhPOP1. Additionally， WRKY70 expression was significantly upregulated under ABA induction. Dual-luciferase reporter assay confirmed that WRKY70 specifically activated the transcriptional activity of the prePhHB promoter （Pro-prePhHB）. ConclusionHB is mainly accumulated in the phloem of P. heterophylla tuberous roots. WRKY70 positively regulates HB biosynthesis by directly activating the promoter activity of prePhHB. This study clarifies the key role of WRKY70 in the regulation of HB biosynthesis and provides an important theoretical basis for the in-depth analysis of the molecular regulatory mechanism underlying HB biosynthesis.

Metabolic dysfunction-associated fatty liver disease （MAFLD） has become one of the most prevalent chronic liver diseases worldwide， posing a serious challenge to public health. In this context， the integration of artificial intelligence （AI）， especially intelligent diagnosis and treatment and digital health interventions based on machine learning， can break through the limitations of traditional methods， realize efficient screening of multi-dimensional data such as key genes， biomarkers， and biochemical metabolites， and achieve revolutionary breakthroughs in risk prediction， subtype identification， and therapeutic effect assessment for MAFLD. This article systematically reviews the ground-breaking application of machine learning models in driving the innovation of clinical diagnosis and precise risk prediction of MAFLD， conducts a comprehensive comparative analysis of digital health practice cases of MAFLD in China and globally， and deeply analyzes their advantages and limitations in terms of research subjects， interventions， and management team. Studies have shown that the deep integration of digital health and long-term management of MAFLD is becoming the key engine driving the transformation of disease management modes towards an intelligent， individualized， and precise era， but there are various ethical and technical issues that need to be addressed urgently.

Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Objective: To optimize the technology and process for recovering immune cells from discarded leukocyte filter through reverse flushing, and to investigate the effects of different reverse flushing solutions and physical conditions (temperature, soaking, and ultrasound) on the cell recovery rate. Additionally, to evaluate the feasibility and quality of isolating and culturing NK cells from the recovered cells. Methods: Normal saline, PBS, and PBS-EDTA were used as reverse flushing solutions to backwash the filter, and the white blood cell recovery rates were compared. The reverse flushing efficiency was optimized by adjusting the temperature of the reverse flushing solution, filter soaking treatment and ultrasonic treatment. The Ficoll separation method was employed to isolate peripheral blood mononuclear cells (PBMCs) from the elution solution and conduct in vitro expansion and culture. Lymphocyte subsets were identified and quantified using flow cytometry. Results: The physiological saline served as the backflush fluid was the most stable. The reverse temperature had a significant impact on the recovery rate of white blood cell subgroups. The recovery rates of lymphocytes and monocytes at 37℃ were significantly higher than those at 4℃ [(35.56±5.55)% vs (22.88±0.31)%, (32.42±4.82)% vs (8.00±1.6)%, t=5.581 and 5.758, respectively, both P<0.001)], and at 25℃ [(35.56±5.55)% vs (22.42±6.13)%, t=5.904, P<0.001; (32.4±4.82)% vs (21.11±1.23)%, t=2.629, P=0.030)]. The recovery rates of white blood cell subgroups after 37℃ immersion were higher than those after direct reverse flow at 37℃, but the difference was not statistically significant (P>0.05). The recovery rate of cells after ultrasonic immersion at 25℃ was further increased compared to that after immersion at 25℃, but the difference was not statistically significant (P>0.05). The purity of the NK cells obtained through sorting reached (94.2±4.5)%, and the viability was (94.8±0.9)%. After 15 days of culture, the cell count was expanded approximately 450 times, yielding more than 10 /mL highly active NK cells. Conclusion: By optimizing the backflushing process, immune cells can be efficiently recovered from discarded filters. The 37℃ backflow liquid has the best backflow effect; soaking and ultrasonic treatment can be used as auxiliary methods to improve recovery rates. The NK cells from this source have high purity, good activity, and strong expansion ability, and can be used as a reliable cell source for immunotherapy research, and in line with the circular economy concept of resource reuse.

With the increasing incidence of lung cancer in the elderly, how to improve the quality and speed of postoperative recovery on the basis of ensuring the therapeutic effect has become an important issue in surgical management. The postoperative recovery process of elderly patients with lung cancer shows higher complexity and challenge due to their unique frailty, comorbidity burden and treatment response. This article will focus on the postoperative rehabilitation strategy, systematically sort out the physiological, pathological and treatment response characteristics of postoperative recovery in elderly patients with lung cancer, propose five postoperative rehabilitation intervention modules based on the enhanced recovery after surgery concept, and further integrate the three challenges of insufficient compliance, research heterogeneity and health economic barriers, and propose a breakthrough method with precise rehabilitation and digital management as the core, providing theoretical support and practical guidance for the optimization and implementation of postoperative rehabilitation programs for elderly patients with lung cancer.

ObjectiveTo investigate the risk factors for plastic bronchitis （PB） in children with Mycoplasma pneumoniae pneumonia （MPP） and to construct a predictive model. MethodsPropensity score matching （1∶4 nearest neighbor matching） was used to balance baseline data between the two groups. Univariate and multivariate Logistic regression analyses were performed to identify independent risk factors. Various machine learning algorithms were applied to build predictive models， and model performance was evaluated using receiver operating characteristic curves， decision curves， and calibration curves. SHapley Additive exPlanations （SHAP） method was used for model interpretation. ResultsAfter matching， baseline characteristics were comparable between the two groups. Compared with the non-PB group， the PB group had significantly longer fever duration， higher incidence of pleural effusion and right upper lobe involvement， and higher levels of procalcitonin （PCT）， D-dimer， lactate dehydrogenase （LDH）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， immunoglobulin E （IgE）， and red blood cell count in bronchoalveolar lavage fluid （BALF） （all P<0.05）， while lymphocyte and eosinophil counts in blood were significantly lower （P<0.05）. Multivariate Logistic regression showed that PCT>0.207 μg/L， LDH>386.25 U/L， right upper lobe involvement， and red blood cell count in BALF>1 500×10⁶ were independent risk factors. Among machine learning models， the gradient boosting machine （GBM） model achieved an area under the curve of 0.786 in the validation set， demonstrating the best generalization ability. SHAP analysis validated the importance of the above variables. ConclusionThe four indicators above have independent predictive value for PB occurrence， and the GBM model shows certain clinical risk stratification capability.