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.

Chronic obstructive pulmonary disease (COPD) is the most common chronic respiratory disease around the world, and pharmacotherapy is the foremost treatment method currently. In recent decades, with the rapid development of bronchoscopic interventional therapy, endoscopic physical ablation technology presents a therapeutic effect in treating COPD, with few treatment-related side effects, showing excellent application prospects in treating COPD. Since ablation techniques in this field are emerging technologies with low patient acceptance, they are not widely used in the clinical treatment of COPD. This article reviews the development process of physical ablation techniques. Moreover, their current application status and the prospects in the field of COPD treatment are also summarized and analyzed. We hope to promote the application of physical ablation in the clinical treatment of COPD and provide practical references and a theoretical basis for the clinical treatment of COPD.

Microorganisms are closely associated with human health, and their pathogenicity is a key factor in various infectious diseases, particularly in dentistry, where they contribute to common conditions such as dental caries, periodontitis, and oral mucosal diseases. Accurate and rapid microbial detection is crucial for early diagnosis, targeted therapy, and disease prevention. Conventional methods, including bacterial culture and molecular biological assays, offer specificity but are limited by long detection cycles, complex procedures, and dependence on laboratory conditions. Terahertz (THz) spectroscopy has emerged as a promising tool in microbial detection due to its non-ionizing nature, high sensitivity, and specific responses to water molecules and biomacromolecules. Integrating THz time-domain spectroscopy, near-field imaging, and metamaterial-enhanced techniques, studies have demonstrated the ability of this approach to effectively distinguish bacteria, fungi, and yeast, differentiate gram-positive and gram-negative bacteria, and even assess bacterial viability. Machine learning has further enhanced feature extraction and classification accuracy, and THz-based methods have shown notable advantages in multi-class microbial identification, detection of antibiotic-resistant strains, and quantitative analysis of microbial concentrations. However, current THz technologies are still constrained by strong water absorption, limited penetration depth, and the lack of standardized spectral databases. Future efforts should focus on mitigating water background interference, improving detection in complex samples, and establishing unified microbial spectral standards. This review systematically summarizes the latest advances of THz technologies in microbial detection, analyzes their mechanisms, advantages, and translational challenges, and proposes directions for future research.

Objective To explore the predictive value of peripheral blood cells in the efficacy of neoadjuvant immunotherapy combined with chemotherapy for esophageal squamous cell carcinoma. Methods A retrospective study was conducted on patients with esophageal squamous cell carcinoma (clinical stages Ⅱ-Ⅳa) who underwent neoadjuvant immunotherapy combined with chemotherapy at the Department of Thoracic Surgery, Affiliated Hospital of North Sichuan Medical College from April 2020 to November 2023. According to whether the pathology was completely relieved after treatment, patients were divided into a pathological complete remission group and a pathological incomplete remission group. The College of American Pathologists criteria were used to evaluate the tumor pathological regression grade (TRG) after neoadjuvant therapy (TRG=0, 1 defined as a good efficacy group, TRG=2, 3 defined as a poor efficacy group). Results A total of 92 patients with esophageal squamous cell carcinoma were collected, including 72 males and 20 females. The average age was (65.86±7.66) years. The complete remission of pathology was closely related to the number of lymphocytes in the blood before treatment (P=0.019). The area under the curve (AUC) for predicting complete remission of esophageal squamous cell carcinoma after neoadjuvant immunotherapy combined with chemotherapy was 0.678, the maximum Youden index was 0.328, and the optimal cutoff value was 1.845. The incidence of postoperative pulmonary infection in the pathological incomplete remission group was higher than that in the pathological complete remission group (25.0% vs. 5.6%, P=0.030). Using the optimal cutoff value, there were statistically significant differences in pathological N stage and pathological TNM stage between patients with lymphocyte counts <1.845×109/L and ≥1.845×109/L (P<0.05). Treatment response (by TRG) was significantly associated with the pretreatment red blood cell count (P=0.009). The AUC for predicting a good TRG response was 0.669, with a maximum Youden index of 0.385 and an optimal cutoff value of 4.235. Between the good and poor response groups, there were statistically significant differences in postoperative pathological T stage (P<0.001), N stage (P=0.041), and TNM stage (P＜0.001). When stratified by the optimal cutoff value, there were statistically significant differences in age (P＜0.001) and the prevalence of hypertension (P=0.022) between patients with red blood cell counts <4.235×1012/L and ≥4.235×1012/L. Conclusion A pretreatment absolute lymphocyte count ≥1.845×109/L and a red blood cell count <4.235×1012/L are good predictors for pathological complete response and a good pathological response, respectively, following neoadjuvant immunotherapy combined with chemotherapy in patients with esophageal squamous cell carcinoma.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

ObjectiveTo apply and systematically evaluate the care-need grading assessment tool for adults with disabilities in welfare institutions. MethodsFrom June to July, 2025, four disability care institutions in Shanghai were selected, and a total of 1 002 adults with disabilities were assessed using the self-developed care-need grading assessment tool for adults with disabilities in welfare institutions. The application effectiveness of the tool was evaluated by analyzing the classification results of care need grading and the reclassification in grade distribution. The application validity was assessed through score differences across functional dimensions, reduced-dimension clustering scatter plots for each grade, and external variables. The application efficiency was evaluated based on the average assessment duration and learning curves. The application utility value was assessed through the distribution characteristics and mapping relationships of service lists across different grades. ResultsThe distribution across disability levels was 84 in Level 1, 298 in Level 2, 92 in Level 3, 246 in Level 4, and 282 in Level 5, indicating a trend where individuals from higher levels in the original system shifted toward the middle and lower levels of the new system. The tool demonstrated strong discriminatory power across the four functional dimensions (P < 0.001), indicating favorable discriminant validity. The five classified levels exhibited clear clustering boundaries in the reduced-dimension space, reflecting robust structural validity. The classification results were consistent with theoretical expectations regarding external variables, including age, disability type, disability grade, number of comorbidities, and primary clinical diagnoses (P < 0.05), demonstrating sound external validity. The median assessment duration was 5.80 minutes, with a significant learning effect (P = 0.037), showcasing high efficiency. Finally, service lists tailored to different care levels were developed, where service content exhibited graded differences across care levels and accurately mapped the care-need characteristics of each grade, reflecting substantial utility value. ConclusionThis tool can classify the care needs of adults with disabilities into five levels, with sound validity and high assessment efficiency; while the resulting service lists for different care levels can be used to guide practical implementation, which can be used for the graded assessment of care needs among adults with disabilities.

Peripheral nerve injury (PNI) severs peripheral connections and induces profound reorganization of primary somatosensory (S1) and motor (M1) cortical maps, a dynamic process that critically shapes the extent and quality of functional recovery. Brain-derived neurotrophic factor (BDNF) has emerged as a central molecular hub linking the initial peripheral insult to subsequent central plastic changes. This review systematically examines BDNF-mediated cortical remodeling following PNI, with a particular emphasis on its spatiotemporally specific regulatory mechanisms and the therapeutic opportunities they present. Immediately after PNI, deafferented cortical territories undergo rapid functional silencing and, over time, become progressively encroached upon by adjacent intact representations. This maladaptive reorganization—characterized by sensory map fusion and motor compensatory invasion—actively impedes successful reinnervation and optimal recovery. Such phenomena have been consistently documented in both non-human primate models and human fMRI studies, spanning sensory and motor modalities. Motor remapping is also prominently observed in facial nerve injury and chronic nerve compression models, underscoring the universality of these plastic changes. Notably, a range of interventions including regional local anesthesia, auditory-tactile substitution, and guided tactile imagery can effectively mitigate this aberrant remodeling, revealing promising avenues for the therapeutic modulation of cortical plasticity during critical post-injury windows. BDNF coordinates post-PNI cortical remodeling through three mechanistically interconnected pathways. First, BDNF drives dendritic and axonal growth via TrkB receptor signaling: retrogradely transported axonal signaling endosomes integrate CREB-dependent transcriptional programs with mTOR-mediated local protein synthesis to bolster dendritic arborization and axonal elongation, while BDNF-induced Limk1 translation precisely fine-tunes actin cytoskeletal dynamics, thereby stabilizing dendritic spine morphology. Second, BDNF governs GABAergic interneuron maturation and perineuronal net formation through the JNK signaling cascade, thereby acting as a “plasticity brake” that preserves the delicate excitatory/inhibitory balance and constrains indiscriminate, maladaptive rewiring. Third, BDNF robustly potentiates NMDAR-dependent long-term potentiation (LTP) by elevating NMDA channel open probability and increasing synaptic receptor density, thus tightly coupling structural remodeling with functional synaptic strengthening. Concurrently, long-term depression pathways are subject to modulation, with NMDAR antagonism exerting time-dependent, bidirectional effects that vary with the post-injury phase. Superimposed on these mechanisms, the functionally antagonistic actions of proBDNF/p75NTR (favoring pruning and growth cone collapse) and mature BDNF/TrkB (promoting survival and stabilization) add further layers of regulatory complexity, highlighting the absolute necessity for precise spatiotemporal control in any therapeutic strategy. Extending our previous experimental findings, we introduce a “cortical reclamation threshold” model. In this framework, early upregulation of BDNF-TrkB signaling enhances inhibitory tone to restrict cortical encroachment by neighboring intact regions, whereas delayed but precisely timed BDNF delivery following surgical nerve repair actively facilitates the reclamation of the original, deafferented cortical maps by regenerating afferent fibers. Importantly, the common BDNF Val66Met polymorphism may significantly modulate individual thresholds, providing a biologically grounded rationale for patient stratification and personalized timing of intervention. Despite this mechanistic promise, clinical translation faces considerable hurdles. These include inherently poor pharmacokinetics of BDNF, severely limited penetration across the blood-brain barrier, dose-dependent neurotoxicity mediated through the p75NTR receptor, and the overarching dual-edged nature of BDNF signaling, which can simultaneously promote both adaptive and maladaptive plasticity. Emerging delivery platforms——including engineered exosomes, polymeric nanoparticles, cryogel microcarriers, and adeno-associated virus (AAV)-based gene therapy——offer potential solutions, but all require rigorous pharmacokinetic, toxicological, and functional validation. Future research priorities should encompass: (1) comprehensive single-cell and spatial transcriptomic mapping to resolve BDNF cellular sources and real-time signaling dynamics across distinct cortical layers and cell types; (2) genotype-stratified dose-response studies to establish safe, effective, and personalized delivery protocols; and (3) large-scale multicenter clinical trials that seamlessly integrate BDNF-targeted interventions with multimodal rehabilitation strategies, such as repetitive transcranial magnetic stimulation and mirror therapy, with longitudinal neuroimaging serving as a biomarker for cortical reclamation. By systematically addressing these priorities, we aim to transform BDNF from a critical endogenous regulator into a precisely controllable and titratable therapeutic target, ultimately enabling a paradigm shift from mere structural repair to true functional neural reconstruction following PNI.

BACKGROUND:The treatment of early knee osteoarthritis can be achieved through two knee preservation treatments:Unicondylar knee arthroplasty and high tibial osteotomy.However,further exploration is needed to determine whether there are differences in knee joint recovery between the two knee preservation surgeries at different stages after surgery. OBJECTIVE:To compare the efficacy and related complications of unicondylar knee arthroplasty and high tibial osteotomy in the treatment of varus osteoarthropathy of the knee,and to provide a reference for clinical decision. METHODS:A total of 103 patients with varus osteoarthritis of the knee underwent surgical treatment in the Affiliated Hospital of Nantong University from September 2018 to September 2022 were selected.Among them,86 patients were followed up for more than 1 year.According to different surgical methods,the patients were divided into unicondylar knee arthroplasty group(49 cases)and high tibial osteotomy group(37 cases).Knee function,pain,and line of force correction were evaluated before surgery,4 weeks,3 months,6 months,and 1 year after surgery in both groups.Hospital for special surgery knee score,functional score of Western Ontario and McMaster Universities Osteoarthritis Index,changes of lateral space of the knee joint,range of motion,proprioception(position sense),and postoperative activity recovery speed were evaluated comprehensively. RESULTS AND CONCLUSION:(1)There were no significant differences in preoperative hospital for special surgery knee score,Western Ontario and McMaster Universities Osteoarthritis Index score and lateral knee compartment size between the two groups.(2)The hospital for special surgery knee score of patients undergoing unicondylar knee arthroplasty was better than that of patients undergoing high tibial osteotomy within 4 weeks after surgery(P<0.05).At 3 and 6 months after surgery,compared with the improvement of the two groups,the hospital for special surgery knee score in the unicondylar knee arthroplasty group was lower than that in the high tibial osteotomy group,and the difference was significant(P<0.05).The range of motion flexion value and position perception of patients undergoing high tibial osteotomy were significantly better than those undergoing unicondylar knee arthroplasty 6 months after surgery(P<0.05).(3)The unicondylar knee arthroplasty group was better than the high tibial osteotomy group in terms of the speed of knee movement recovery(P<0.05).(4)However,there was no significant difference between the two groups in the change of hospital for special surgery knee score,range of motion,and the width of lateral knee space during 1-year follow-up.(5)All patients were followed up for more than 1 year,and no adverse complications were found during the follow-up.(6)It is indicated that the short-term effect of knee functional recovery in patients with high tibial osteotomy is better than that in patients with unicondylar knee arthroplasty,but there is no significant difference in medium-and long-term efficacy between the two kinds of surgery for medial knee arthritis.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.