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: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing

Objective:To explore the application value of three-dimensional high-resolution anorectal manometry(3D-HRAM)model in the diagnosis and localization of anal sphincter injury after surgery for complex anal fistula.Methods:A prospective study was con-ducted on 92 patients who had undergone surgery for complex anal fistula in the Department of Coloproctology of The People's Hospi-tal Affiliated to Fujian University of Traditional Chinese Medicine from January 2023 to January 2024.The study was conducted in two stages.In the first stage,92 patients underwent 3D-HRAM and endoanal ultrasonography(EAUS)to examine the sphincter,and the data were compared with intraoperative records to evaluate the diagnostic efficiency and localization accuracy of 3D-HRAM and EAUS.In the second stage,92 patients who had been examined were grouped according to the presence or absence of symptoms of anal dysfunction to further verify the diagnostic and localization values of 3D-HRAM and EAUS for postoperative compensated/decompen-sated sphincter injury.Results:Among 92 patients,41 and 57 patients were diagnosed with sphincter injury through 3D-HRAM and EAUS,with a sensitivity of 61.19%and 85.07%,a specificity of 88%and 76%,an area under the curve of 0.739 and 0.813 calcu-lated by plotting the receiver operating characteristic curve,and a localization accuracy of 44.77%and 71.64%,respectively,showing significant differences between 3D-HRAM and EAUS(P=0.002),indicating that 3D-HRAM had lower diagnostic efficiency and local-ization accuracy than EAUS for anal sphincter injury after surgery for complex anal fistula.After grouping by symptoms,the diagnostic efficiency and localization accuracy of 3D-HRAM for symptomatic sphincter injury(decompensated)were significantly better than those for asymptomatic sphincter injury,and were similar to those of EAUS(P=0.763).Conclusion:The application advantage of 3D-HRAM lies in the diagnosis and localization of decompensated anal sphincter injury after surgery for complex anal fistula,which provides effective technical support for the study of anal defecation control mechanisms and injury compensation mechanisms.

An effective method for simultaneously detecting four semivolatile earthy-musty odors in freshwater fish by gas chromatography-mass spectrometry(GC-MS)was developed.The concurrent extraction of geosmin(GSM),2-methylisoborneol(MIB),2-isopropyl-3-methoxypyrazine(IPMP),and 2-isobutyl-3-methoxypyrazine(IBMP)in fish tissue was conducted with n-hexane.The optimized QuEChERS material was implemented,and it was found that C18,primary secondary amine(PSA)and MgSO4 could adsorb the target analytes in n-hexane.So only the graphitized carbon black(GCB)could be used to purify the extraction.The adsorption rates of different materials for the four kinds of odors materials were explored in n-hexane and ethyl acetate.The experimental results revealed that the adsorption rates of silica for the four targets were 99.5%-100%in n-hexane and 0.7%-5.0%in ethyl acetate respectively.Then the silica solid phase extraction(SPE)method was utilized to eluent the compounds using 1.0 mL n-hexane/ethyl acetate in different proportions.The results of the comparative analysis demonstrated that n-hexane/ethyl acetate(4∶1,V/V)was the optimized eluent.Based on the obtained results,n-hexane extraction and GCB purification combined with silica SPE were used to isolate GSM,MIB,IPMP and IBMP from fish and the method was validated.It was found that the method showed good linearity in the range of 0.5-200 ng/mL,and with detection limits of 0.6 μg/kg for GSM and MIB,0.2 μg/kg for IPMP and IBMP.The limits of quantitation(LOQ)were 1.0 μg/kg for GSM and MIB,0.6 μg/kg for IPMP and IBMP.Good recoveries(77.5%-112.0%)and relative standard deviations(1.56%-9.42%)were also obtained.The use of silica SPE greatly mitigated the issue that the off-flavor compounds were easily lost in the gas blowing concentration process.There was no cross contamination in this method because the sample pretreatments were conducted separately,which was different with the most commonly used HS-SPME method for detecting semi-volatile substances.The sensitivity of this method was high enough to produce good quantitative results below the odor thresholds of the examined off-flavor compounds.

Objective:To evaluate the efficacy and safety of anlotinib neoadjuvant therapy for newly diagnosed locally advanced thyroid cancer (LATC).Methods:Twenty-four newly diagnosed LATC patients (10 males and 14 females, age (47.1±3.3) years) admitted to Affiliated Hospital of Integrated Traditional Chinese and Western Medicine of Nanjing University of Chinese Medicine were prospectively included from January 2023 to April 2024. Patients were given anlotinib neoadjuvant therapy (12mg/d, 2 weeks of medication, 1 week of discontinuation), and the efficacy of the treatment was evaluated by CT and multi-disciplinary treatment at the end of each treatment cycle. Patients assessed as suitable for surgery would be scheduled for surgery, while those who were not suitable for surgery would continue to receive neoadjuvant therapy and periodic evaluations. The primary endpoints were objective response rate (ORR) and disease control rate (DCR), and the R0/1 resection rate and adverse events (AE) after neoadjuvant therapy were observed. Paired- t test was used to analyze the differences between groups, and the Clopper-Person accurate method was used to calculate the bilateral 95% CI of ORR and other indicators. Results:Twenty-four patients received 2(2, 3) cycles of neoadjuvant therapy with anlotinib, of which 23 underwent surgery after anlotinib therapy. After neoadjuvant therapy, the mean maximum diameter of target lesions decreased by 23.5%(95% CI: 2.8%-44.3%) compared with baseline ( t=9.22, P<0.001). The ORR and DCR were 37.5%(95% CI: 18.8%-59.4%) and 100%(95% CI: 85.8%-100%), respectively. About 91.7%(95% CI: 73.0%-99.0%) of patients eventually underwent R0/1 resection. Hand and foot skin reactions, hypertension, oral mucositis, and leukopenia were common AE; grade 4 and 5 AE were not observed. Conclusion:Anlotinib can be safely used as neoadjuvant therapy for newly diagnosed LATC patients with good antitumor effects, providing better surgical opportunities for R0/1 resection.

Objective:To explore the effect of combining repeated peripheral (rPMS) and central transcranial magnetic stimulation (rTMS) in treating upper limb motor dysfunction after a stroke.Methods:Seventy-eight patients with upper limb motor dysfunction after a stroke were randomly divided into a control group, an rTMS group and a combined magnetic stimulation group, each of 26. All three groups underwent routine rehabilitation, while the rTMS group was repeatedly given low frequency transcranial magnetic stimulation of the M1 region on the unaffected side, and the combined group also received repeated peripheral magnetic stimulation at Erb′s point on the affected upper limb. There was one treatment session a day, 5 days a week for 3 weeks. Before and after the treatment, everyone′s upper limb motor function was quantified using the Fugl-Meyer upper extremity assessment (FMA-UE) and the Wolf motor function test (WMFT). Skill in the activities of daily living was quantified in terms of a Barthel index (BI). Motor recovery of the upper limbs and hands was assessed using Brunnstrom staging. The latency and amplitude of the motor evoked potentials (MEPs) in the subjects′ affected abductor pollicis brevis muscles were also recorded before and after the treatment. Pearson correlation coefficients quantified the correlation between the changes in FMA-UE scores and MEP amplitudes before and after the treatment in the three groups.Results:There were no significant differences among the three groups before the treatment. Afterward, however, the average FMA-UE, WMFT and BI scores, as well as the upper limb and hand Brunnstrom stages and the average MEP latencies and amplitudes of all the three groups had improved significantly. The combined group′s average results were then significantly better than the other two groups′ averages, except for the upper limb Brunnstrom stages. The increases in MEP amplitude were positively correlated with the increases in FMA-UE scores among the rTMS and the combined group, but there was no significant correlation between them in the control group.Conclusions:The combined application of rPMS and contralateral low frequency rTMS can effectively relieve motor dysfunction in the upper limbs in the early stages after a stroke.

Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation (CV) for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Isoflavones which mainly distributed in leguminous plants have plenty of health benefits.Isoflavone synthase(IFS)is a membrane-associated cytochrome P450 enzyme(CYP450)which carries out the unique aryl-ring migration and hydroxylation.So far,few crystal structures of plant P450s have been obtained.We determined the crystal structure of IFS from Medicago truncatula at 1.9 ? by MAD method using a selenomethionine substituted crystal and conducted molecular docking and mutagenesis study.The structure of IFS complexed with imidazole exhibits the helix Ⅰa-loop-helix Ⅰβ motif which cor-responds to helix Ⅰ of other P450s.Compared with structures of common P450s,IFS/imidazole structure contains an extra domain,i.e.,the γ-domain.The structure reveals a homodimer in which the γ-domain of one molecule interacts with the β-domain of another.The plane of heme group makes an angle of ap-proximately 40° with the helix Ⅰa-loop-helix Ⅰβ motif.Molecular docking combined with mutagenesis study suggested that Trp-128 and Asp-300 might play important roles in substrate binding and recogni-tion.Phe-301,Ser-303 and Gly-305 from the helix Ⅰa-loop-helix Ⅰβ motif may play important roles in the aryl-ring migration.These novel structural features reveal insights into the unique reaction mechanism of IFS and provide a basis for engineering IFS in leguminous crops for health purpose.