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.

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 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.

Environmental toxicants have been linked to aging and age-related diseases. The emerging evidence has shown that the enhancement of detoxification gene expression is a common transcriptome marker of long-lived mice, Drosophila melanogaster, and Caenorhabditis elegans. Meanwhile, the resistance to toxicants was increased in long-lived animals. Here, we show that farnesoid X receptor (FXR) agonist obeticholic acid (OCA), a marketed drug for the treatment of cholestasis, may extend the lifespan and healthspan both in C. elegans and chemical-induced early senescent mice. Furthermore, OCA increased the resistance of worms to toxicants and activated the expression of detoxification genes in both mice and C. elegans. The longevity effects of OCA were attenuated in Fxr ^-/- mice and Fxr homologous nhr-8 and daf-12 mutant C. elegans. In addition, metabolome analysis revealed that OCA increased the endogenous agonist levels of the pregnane X receptor (PXR), a major nuclear receptor for detoxification regulation, in the liver of mice. Together, our findings suggest that OCA has the potential to lengthen lifespan and healthspan by activating nuclear receptor-mediated detoxification functions, thus, targeting FXR may offer to promote longevity.

Objective To explore the value of 3D printing technology in transcatheter aortic valve replacement(TAVR)for bicuspid aortic stenosis.Methods We retrospectively analyzed the clinical data of patients who underwent TAVR for bicuspid aortic stenosis at the Department of Cardiac Surgery of the Second Hospital of Hebei Medical University between January 2020 and January 2023.Seven-ty patients were divided into 3D printing and non-3D printing groups of 35 each,based on whether or not 3D printing technology was applied,and the perioperative clinical data of the two groups were compared.Results The patients' postoperative symptoms signifi-cantly improved compared with those before the operation,and the left ventricular ejection fraction increased to varying degrees.Compared with the non-3D printing group,the operation time,X-ray irradiation time.and transvalvular time in the 3D printing group were signifi-cantly shortened,and the probabilities of the occurrence of postoperative"flap-to-flap"implantation and conduction block were signifi-cantly reduced,with statistically significant differences(P＜0.05).There was no statistically significant difference(P＞0.05)in the inci-dence of moderate and above perivalvular leakage,valve displacement,or conversion to thoracotomy between the two groups after surgery.Conclusion 3D printing technology can effectively guide the TAVR treatment of bicuspid aortic stenosis.While significantly shortening the operation time,it can effectively increase the success rate of TAVR and reduce the risk of adverse events,providing a new approach for the transcatheter treatment of bicuspid aortic stenosis.

OBJECTIVE To establish a closed-loop management system for the whole-process traceability of outpatient drugs based on internet of things(IoT)and blockchain technology,and evaluate its implementation effects.METHODS A closed-loop management system for the whole-process traceability of outpatient drugs covering the entire drug lifecycle was designed using drug traceability codes integrated with IoT and blockchain technology.System effectiveness was evaluated from three dimensions:work efficiency,medication management quality and data safety by comparing indicators such as the acceptance time of incoming drugs and the number of collected drug traceability codes before the system implementation(October to December 2024)and after the system implementation(January to March 2025).RESULTS A closed-loop management system for the whole-process traceability of outpatient drugs,centered around the drug traceability code management system,was successfully established.The acceptance time for incoming drugs was shortened from(4.65±0.26)h before implementation to(0.34±0.08)h after implementation(P＜0.05).The number of collected drug traceability codes increased from 419 018 to 1 236 522,and the coverage rate of traceability codes rose from 28.36%to 89.88%(P＜0.05).The time pharmacists spent on drug expiry management per week decreased from(128.40±19.20)min to(0.56±0.13)min(P＜0.05),and the dispensing time for a single prescription(excluding a part of injections and repackaged drugs)was reduced from(143.25±17.67)s to(15.24±10.08)s(P＜0.05).The time for drug return was reduced from 129.90(122.32,137.00)s to 104.36(89.91,117.33)s(P＜0.05);the number of drug dispensing errors decreased from 2 cases to 0 cases.After the system was launched,there were no data security incidents in our outpatient pharmacy.CONCLUSIONS The constructed closed-loop management system for the whole-process traceability of outpatient drugs can significantly enhance drug traceability accuracy and drug management quality,improve pharmacist work efficiency,and reduce drug management risks,thus providing a feasible solution for the digital transformation of hospital pharmaceutical services.

Objective To explore the value of 3D printing technology in transcatheter aortic valve replacement(TAVR)for bicuspid aortic stenosis.Methods We retrospectively analyzed the clinical data of patients who underwent TAVR for bicuspid aortic stenosis at the Department of Cardiac Surgery of the Second Hospital of Hebei Medical University between January 2020 and January 2023.Seven-ty patients were divided into 3D printing and non-3D printing groups of 35 each,based on whether or not 3D printing technology was applied,and the perioperative clinical data of the two groups were compared.Results The patients' postoperative symptoms signifi-cantly improved compared with those before the operation,and the left ventricular ejection fraction increased to varying degrees.Compared with the non-3D printing group,the operation time,X-ray irradiation time.and transvalvular time in the 3D printing group were signifi-cantly shortened,and the probabilities of the occurrence of postoperative"flap-to-flap"implantation and conduction block were signifi-cantly reduced,with statistically significant differences(P＜0.05).There was no statistically significant difference(P＞0.05)in the inci-dence of moderate and above perivalvular leakage,valve displacement,or conversion to thoracotomy between the two groups after surgery.Conclusion 3D printing technology can effectively guide the TAVR treatment of bicuspid aortic stenosis.While significantly shortening the operation time,it can effectively increase the success rate of TAVR and reduce the risk of adverse events,providing a new approach for the transcatheter treatment of bicuspid aortic stenosis.

Activation of nuclear factor erythroid 2-related factor 2(Nrf2)by Kelch-like ECH-associated protein 1(Keap1)alkylation plays a central role in anti-inflammatory therapy.However,activators of Nrf2 through alkylation of Keap1-Kelch domain have not been identified.Deoxynyboquinone(DNQ)is a natural small molecule discovered from marine actinomycetes.The current study was designed to investigate the anti-inflammatory effects and molecular mechanisms of DNQ via alkylation of Keap1.DNQ exhibited signif-icant anti-inflammatory properties both in vitro and in vivo.The pharmacophore responsible for the anti-inflammatory properties of DNQ was determined to be the α,β-unsaturated amides moieties by a chemical reaction between DNQ and N-acetylcysteine.DNQ exerted anti-inflammatory effects through activation of Nrf2/ARE pathway.Keap1 was demonstrated to be the direct target of DNQ and bound with DNQ through conjugate addition reaction involving alkylation.The specific alkylation site of DNQ on Keap1 for Nrf2 activation was elucidated with a synthesized probe in conjunction with liquid chromatography-tandem mass spectrometry.DNQ triggered the ubiquitination and subsequent degra-dation of Keap1 by alkylation of the cysteine residue 489(Cys489)on Keap1-Kelch domain,ultimately enabling the activation of Nrf2.Our findings revealed that DNQ exhibited potent anti-inflammatory capacity through α,β-unsaturated amides moieties active group which specifically activated Nrf2 signal pathway via alkylation/ubiquitination of Keap1-Kelch domain,suggesting the potential values of targeting Cys489 on Keap1-Kelch domain by DNQ-like small molecules in inflammatory therapies.