Objective To evaluate the short-term efficacy of transcatheter aortic valve replacement (TAVR) using Venus A-Plus valve delivery system in patients with severe aortic stenosis. Methods The clinical data of patients undergoing TAVR in our hospital from August 2018 to March 2022 were collected and they were divided into a Venus A-Plus and a Venus A group according to the type of valve delivery system used. The perioperative data of the two groups were compared. Results A total of 121 patients were included, including 70 patients in the Venus A-Plus group [45 males and 25 females with a mean age of (67.81±6.62) years], and 51 patients in the Venus A group [33 males and 18 females with a mean age of (68.25±7.01) years]. All patients underwent TAVR, and the postoperative hemodynamic features (left ventricular ejection fraction, mean cross-valve pressure difference, peak flow rate) were significantly improved (P<0.05). There was no statistical difference in surgical success rate, all-cause mortality, conversion to thorax opening, valve-in-valve placement, moderate or above perivalvular regurgitation, new left bundle branch block or new right bundle branch block between the two groups (P>0.05). Conclusion TAVR with Venus A-Plus valve delivery system in patients with severe aortic stenosis shows comparable efficacy to the first-generation Venus A system and is satisfactory, safe and reliable.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Background Bufei Huoxue Capsule (BHC) has gradually been used in clinical practice to treat patients with pneumoconiosis in recent years. However, the comprehensive evaluation of its efficacy and safety is lacking. Objective To systematically assess the therapeutic potential of BHC for pneumoconiosis. Methods By searching 9 databases, e.g. China National Knowledge Infrastructure, Wanfang Database, VIP Chinese Science and Technology Journals Database, SinoMed, Yiigle, PubMed, Embase, Cochrane Library, and Web of Science, randomized controlled trials (RCTs) related to the use of BHC for the treatment of pneumoconiosis were identified. The search covered the period from the inception of these databases to August 31, 2025. This systematic review conformed to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) 2020. The included studies underwent quality appraisal by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Subgroup analysis and sensitivity analysis were applied to assess the robustness of results and explore the potential heterogeneity among the studies. Results A total of 19 RCTs were included and all were reported in Chinese. The therapy containing BHC showed a superior impact on forced expiratory volume in one second (FEV₁) (95%CI: 0.38, 0.66; I²=69%, P<0.05), FEV₁% (95%CI: 3.37, 5.72; I²=12%, P<0.05), forced vital capacity (FVC) (95%CI: 0.34, 0.45; I²=0%, P<0.05), FEV₁/FVC% (95%CI: 6.29, 10.35; I²=21%, P<0.05), 6-minute walking distance (6MWD) score (95%CI: 16.32, 27.64; I²=22%, P<0.05), St. George's Respiratory Questionnaire (SGRQ) score (95%CI: −1.47, −1.05; I²=13%, P<0.05), and total effective rate (95%CI: 2.71, 6.78; I²=0%, P<0.05) in patients with pneumoconiosis. In addition, BHC had less adverse reactions reported (95%CI: 0.69, 1.74; I²=0%, P=0.70). Conclusions Combined BHC therapy can significantly improve the lung function and the quality of life in patients with pneumoconiosis, with a good safety profile. However, high-quality RCTs with multicenter, large-sample, double-blind, and standardized protocols still need to be conducted in the future to provide more reliable evidence.

Objective: To establish a method for determining the molecular weight and molecular weight distribution of Poly(Lactide-co-Glycolide Acid) (PLGA) using Size Exclusion Chromatography-Refractive Index-Multiangle Laser Light Scattering (SEC-RI-MALLS) and Size Exclusion Chromatography-Refractive Index (SEC-RID), and to compare the results obtained from these two methods.
Methods: For SEC-RI-MALLS, tetrahydrofuran was used as the mobile phase, Shodex GPC KF-803L was employed as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, and an injection volume of 100 μL. For SEC-RID, tetrahydrofuran was also used as the mobile phase, Agilent PLgel 5 μm MIXD-D was used as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, differential detector temperature at 35 ℃, and an injection volume of 20 μL. The molecular weight and molecular weight distribution were calculated using Agilent’s GPC software. The newly established methods were validated methodologically, and the molecular weight and molecular weight distribution of 13 batches of samples were determined.
Results: The precision, accuracy, stability, and repeatability tests for SEC-RI-MALLS showed RSD values of 1.35%, 1.58%, 1.53%, and 1.26%, respectively. The SEC-RID method exhibited good linearity (r=0.999 9), with RSD values for precision, accuracy, stability, and repeatability tests (n=6) of 2.05%, 1.62%, 1.30%, and 2.97%, respectively. The results obtained from SEC-RI-MALLS were lower than those from SEC-RID, and the molecular weight distribution coefficient was smaller, but the results from the paired T-test performed with the value measured by SEC-RID method and the value measured by SEC-RI-MALLS method multiplied a conversion coefficient of 1.5 showed no significant difference between the two methods.
Conclusion: Both methods are stable and reliable, and can be used for the determination of PLGA molecular weight and molecular weight distribution based on the specific situations.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

Objective To investigate the new-onset conduction block after transcatheter aortic valve replacement (TAVR) and summarize the relevant experience. Methods The perioperative data of TAVR patients in the Second Hospital of Hebei Medical University from January 2016 to February 2023 were collected, and the new-onset incidence of conduction block after TAVR was analyzed retrospectively. Results Finally 352 patients were included, including 225 males and 127 females, with an average age of (67.2±5.1) years, among whom 256 patients were treated with Venus-A valves, 69 patients with Vita-Flow valves, and 27 patients with J-Valve valves. There were 38 (10.8%) patients of new-onset postoperative block. There were 6 (1.7%) patients of new-onset postoperative grade Ⅲ atrioventricular block, including 5 (2.0%) patients of Venus-A and 1 (1.4%) patient of Vita-Flow. Conduction function was restored in 2 patients within 14 days after surgery, and failed to be restored in 4 patients, who then received permanent pacemaker implantation in the Department of Cardiology. There were 27 (7.7%) patients of new left bundle branch block after surgery, including 22 (8.6%) patients of Venus-A, 4 (5.8%) patients of Vita-Flow and 1 (3.7%) patient of J-Valve; and conduction function was restored within 7 days after surgery in 23 patients, and 5 (1.4%) patients developed new right bundle branch blocks after surgery including 4 (1.5%) patients of Venus-A and 1 (1.4%) patient of Vita-Flow. Conclusion New-onset conduction block is a common complication after TAVR, and the new-onset rate of left bundle branch block is the highest, followed by the grade Ⅲ atrioventricular block. Mastering reasonable methods and applying appropriate strategies can effectively reduce the new-onset rate of postoperative conduction block and improve the overall success rate of TAVR surgery.

Angle class Ⅱ malocclusion is often characterized by mandibular retraction and lip incompetence,which affects the patient's lateral appearance and may even lead to upper airway stenosis.It can be classified into dental and skeletal types.For skeletal class Ⅱ malocclusion patients with mandibular retraction during the peak growth period,mandibular anterior guidance with a functional orthodontic appliance is generally considered as the optimal clinical treatment approach.At present,there remains a paucity of clinical reports on the clinical application of bracket-free clear aligners in mandibular anterior guidance,both domestically and internationally.This article presented a case of an adolescent patient with skeletal class Ⅱ malocclusion accompanied with deep overbite treated with bracket-free clear aligner for mandibular anterior guidance in combination with intermaxillary class Ⅱ traction.During the treatment,vertical correction involved anterior intrusion of the anterior teeth to improve the deep overbite,while horizontal correction included maxillary and mandibular expansion to coordinate the width of the dental arches,and asymmetric anterior guidance was used to correct the midline deviation.After 35 months of treatment,the patient's convex facial profile and mandibular retrusion were significantly improved.The subspinale-nasion-supramentale angle(ANB)was decreased from 6.8° to 3.9°,the overbite and overjet were normalized,and the bilateral canine and molar reached a neutral relationship.The mentolabial sulcus depth(Si-LiPg′)and the soft tissue thickness of pogonion to pogonion(Pm-Pm′)were decreased,resulting in a shallower mentolabial sulcus and a more harmonized lateral facial soft tissue profile.The mandibular incisor to mandibular plane angle(IMPA)was decreased from 116.6° to 110.7°,indicating retraction of the lower incisors during mandibular anterior guidance.In conclusion,the orthodontic strategy of mandibular advancement with clear aligners in skeletal class Ⅱ malocclusion patients can avoid excessive overcompensation of the upper and lower anterior teeth and shorten the orthodontic treatment cycle.

OBJECTIVE: To systematically evaluated clinical efficacy of Kirschner's needle and elastic intramedullary nail fixation in treating proximal humeral fractures in children by Meta-analysis. METHODS: Literature on the treatment of proximal humeral fractures in children with Kirschler needles and elastic intramedullary nails published on Wanfang, VIP, CNKI and China biology medicine (CBM), PubMed, Embase, and Web of Science databases were searched from the establishment of databases to October, 2023. Literature extraction, management and data entry were performed by Endnote X9 and Excel 2019, and Meta-analysis was conducted by RevMan 5.3 software. The operation time, hospital stay, fracture healing time, shoulder joint extension range of motion, disabilities of arm, shoulder and hand(DASH) questionnaire score, Neer score or Constant-Murley score and complications were compared between two groups. RESULTS: A total of 7 literatures were included, 1 was prospective study, 6 were retrospective cohort study. There were 521 children, 264 children in Kirschner wire group and 257 children in elastic intramedullary nail fixation group. The results of Meta analysis showed operation time[WMD=-12.61, 95%CI(-24.89, -0.33), P=0.04], fracture healing time[WMD=-0.26, 95%CI(-0.49, -0.02), P=0.03], total complication rate [OR=6.83, 95%CI(3.33, 14.01), P<0.001], nail tract infection rate[OR=6.77, 95%CI(1.72, 26.69), P=0.006] and displacement fracture rate[OR=3.57, 95%CI(1.35, 9.44), P=0.01] between two groups had statistically differences(P>0.05), while there were no statistically significant difference in comparison of hospital stay, shoulder joint extension range of motion, DASH, Neer score, Constant-Murley score, and incidence of skin irritation between two groups (P>0.05). CONCLUSION Kirschner's needle internal fixation has a short operation time and simple operation, but it has a higher incidence of complications compared with elastic nail internal fixation technique. In terms of efficacy and safety, elastic intramedullary nail fixation is one of the options for the treatment of proximal humeral fractures in children.
Humans ; Fracture Fixation, Intramedullary/instrumentation* ; Child ; Shoulder Fractures/physiopathology* ; Bone Nails ; Bone Wires ; Male ; Needles ; Female