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.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, which increases the incidence of colorectal cancer (CRC). In the pathophysiology of IBD, ubiquitination/deubiquitination plays a critical regulatory function. Josephin domain containing 2 (JOSD2), a deubiquitinating enzyme, controls cell proliferation and carcinogenesis. However, its role in IBD remains unknown. Colitis mice model developed by dextran sodium sulfate (DSS) or colon tissues from individuals with ulcerative colitis and Crohn's disease showed a significant upregulation of JOSD2 expression in the macrophages. JOSD2 deficiency exacerbated the phenotypes of DSS-induced colitis by enhancing colon inflammation. DSS-challenged mice with myeloid-specific JOSD2 deletion developed severe colitis after bone marrow transplantation. Mechanistically, JOSD2 binds to the C-terminal of inosine-5'-monophosphate dehydrogenase 2 (IMPDH2) and preferentially cleaves K63-linked polyubiquitin chains at the K134 site, suppressing IMPDH2 activity and preventing activation of nuclear factor kappa B (NF-κB) and inflammation in macrophages. It was also shown that JOSD2 knockout significantly exacerbated increased azoxymethane (AOM)/DSS-induced CRC, and AAV6-mediated JOSD2 overexpression in macrophages prevented the development of colitis in mice. These outcomes reveal a novel role for JOSD2 in colitis through deubiquitinating IMPDH2, suggesting that targeting JOSD2 is a potential strategy for treating IBD.

Arson is classified as a violent crime,and often involves accelerants that significantly increase casualties and property damage.These accelerants,typically flammable liquids with low saturated vapor pressure,present volatile characteristic components in fire residues,making evidence preservation critical for accurate forensic analysis.In this study,the preservation performance of AMPAC(American KAPAC polyester sampling bags)and polyethylene(PE)evidence bags were evaluated under simulated field conditions(40 oC)through gas chromatography-mass spectrometry(GC-MS)technique,focusing on background interference,sealing integrity,and cross-contamination.The results demonstrated that AMPAC bags exhibited minimal background interference(C12?C14 alkanes detected after 3?7 days)and effective gasoline sealing,though slight losses of C2?C3 alkylbenzenes and trace cross-contamination were observed.In contrast,PE bags showed significant background hydrocarbons(C15?C19 alkanes)and pronounced gasoline component losses,including C2?C4 alkylbenzenes,naphthalenes,and indenes.Notably,severe cross-contamination of gasoline markers was detected in adjacent blank PE bags,with characteristic components such as C2?C4 alkylbenzenes,naphthalenes,methylnaphthalenes,dimethylnaphthalenes,indenes,indanes,methylindenes,and dimethylindenes identified,indicating substantial cross-contamination issues in PE evidence bags.Microstructural analysis revealed superior sealing in AMPAC bags attributed to their smooth,dense surface morphology compared to PE's rougher,porous structure.This study established a comprehensive evaluation framework for fire residue evidence containers,and found that PE bags were unsuitable for long-term gasoline evidence preservation due to compromised integrity.These findings provided critical references for forensic container selection in fire investigations.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

Objective To investigate the relationship between plasma dipeptidyl peptidase 4 (DDP4) level and the progression of abdominal aortic aneurysm. Methods Forty-three patients with abdominal aortic aneurysm admitted to Baoji Central Hospital from January 2020 to May 2021 were selected. The follow-up was conducted at least 12 months,the absolute measurement of the maximum anterior-posterior diameters of the aneurysm and the rate of progression were obtained based on the first and last computed tomography angiography data,and the patients were divided into the progression group (with the rate of progression≥0.5 mm/year) and the progression-free group (with the rate of progression<0.5 mm/year) according to the rate of the abdominal aortic aneurysm progression. The clinical characteristics of the two groups were compared. Plasma DDP4 levels were detected by enzyme-linked immunosorbent assay. The correlation between plasma DDP4 and the rate of abdominal aortic aneurysm progression was analyzed by Pearson correlation and multiple linear regression. The predictive performance of plasma DDP4 on abdominal aortic aneurysm progression was analyzed by Logistic regression model and receiver operating characteristic (ROC) curve. Results The thickness of intracavitary thrombus (P=0.046) and the rate of abdominal aortic aneurysm progression (P<0.001) in the progression group were greater/faster than those in the the progression-free group,and the plasma level of DDP was significantly higher than that in the progression-free group (P<0.001). Multivariate Logistic regression analysis showed that plasma DDP4 level was an independent predictor of abdominal aortic aneurysm progression (P<0.05). Pearson correlation analysis showed that plasma DDP4 level was positively correlated with the rate of abdominal aortic aneurysm progression (r=0.517,P<0.001). After adjusting for other confounding factors,multiple linear regression showed that there was still a significantly positive correlation between plasma DDP4 level and abdominal aortic aneurysm progression rate (β=0.312,95％CI:0.002 to 0.484,P=0.048). The area under the curve of baseline plasma DDP4 level for predicting abdominal aortic aneurysm progression was 0.840 (95％CI:0.704 to 0.976),with corresponding cutoff value of 13.89 pg/mL,specificity of 85.7％,and sensitivity of 79.3％. Conclusion Elevated plasma DDP4 levels in patients with abdominal aortic aneurysm are associated with a higher risk of aneurysm progression. Plasma DDP4 is expected to be a predictive biomarker for abdominal aortic aneurysm progression.

Objective To investigate the correlation between PPARγ and female interstitial cystitis/bladder pain syndrome (IC/BPS) and to establish a predictive model. Methods Clinical data were collected from 89 female IC/BPS patients (observational group) admitted to the hospital from June 2022 to December 2023,and 90 healthy female volunteers undergoing physical examinations during the same period (control group). Plasma levels of inflammatory factors,total antioxidant capacity (TAC),total glutathione (GSH),malondialdehyde (MDA),and PPARγ levels were measured. Significant clinical features were identified using LASSO regression and fitted into a multivariate logistic regression model. The diagnostic efficacy was assessed through receiver operat-ing characteristic (ROC) curves. Results Compared to the control group,the observation group exhibited signifi-cantly elevated age,BMI,NLR,absolute neutrophil count,IFN-α,IL-1β,IL-6,IL-8,TNF-α and CD3+CD4+T expression levels,while absolute lymphocyte count,IL-10,TAC,GSH and plasma PPARγ expression levels were significantly decreased (all P<0.05). LASSO regression identified 8 variables,including NLR,IFN-α,absolute neutrophil count,IL-1β,IL-6,TNF-α,CD3+CD4+T and PPARγ,which were incorporated into the predictive model. Multivariate binary logistic regression analysis revealed that elevated levels of IL-1β,TNF-α and CD3+CD4+T cells,along with reduced PPARγ levels,were independent risk factors for IC/BPS. ROC curve analy-sis indicated that the diagnostic efficacy of the combined PPARγ and clinical parameters (age,IL-1β,TNF-α and CD3+CD4+T) (AUC=0.901) was superior to PPARγ alone (AUC=0.839). Conclusion Plasma PPARγ levels are significantly reduced in female IC/BPS patients and serve as a potential diagnostic marker,with combined clinical parameters enhancing diagnostic accuracy.

Objective To investigate the correlation between PPARγ and female interstitial cystitis/bladder pain syndrome (IC/BPS) and to establish a predictive model. Methods Clinical data were collected from 89 female IC/BPS patients (observational group) admitted to the hospital from June 2022 to December 2023,and 90 healthy female volunteers undergoing physical examinations during the same period (control group). Plasma levels of inflammatory factors,total antioxidant capacity (TAC),total glutathione (GSH),malondialdehyde (MDA),and PPARγ levels were measured. Significant clinical features were identified using LASSO regression and fitted into a multivariate logistic regression model. The diagnostic efficacy was assessed through receiver operat-ing characteristic (ROC) curves. Results Compared to the control group,the observation group exhibited signifi-cantly elevated age,BMI,NLR,absolute neutrophil count,IFN-α,IL-1β,IL-6,IL-8,TNF-α and CD3+CD4+T expression levels,while absolute lymphocyte count,IL-10,TAC,GSH and plasma PPARγ expression levels were significantly decreased (all P<0.05). LASSO regression identified 8 variables,including NLR,IFN-α,absolute neutrophil count,IL-1β,IL-6,TNF-α,CD3+CD4+T and PPARγ,which were incorporated into the predictive model. Multivariate binary logistic regression analysis revealed that elevated levels of IL-1β,TNF-α and CD3+CD4+T cells,along with reduced PPARγ levels,were independent risk factors for IC/BPS. ROC curve analy-sis indicated that the diagnostic efficacy of the combined PPARγ and clinical parameters (age,IL-1β,TNF-α and CD3+CD4+T) (AUC=0.901) was superior to PPARγ alone (AUC=0.839). Conclusion Plasma PPARγ levels are significantly reduced in female IC/BPS patients and serve as a potential diagnostic marker,with combined clinical parameters enhancing diagnostic accuracy.

Objective To investigate the relationship between plasma dipeptidyl peptidase 4 (DDP4) level and the progression of abdominal aortic aneurysm. Methods Forty-three patients with abdominal aortic aneurysm admitted to Baoji Central Hospital from January 2020 to May 2021 were selected. The follow-up was conducted at least 12 months,the absolute measurement of the maximum anterior-posterior diameters of the aneurysm and the rate of progression were obtained based on the first and last computed tomography angiography data,and the patients were divided into the progression group (with the rate of progression≥0.5 mm/year) and the progression-free group (with the rate of progression<0.5 mm/year) according to the rate of the abdominal aortic aneurysm progression. The clinical characteristics of the two groups were compared. Plasma DDP4 levels were detected by enzyme-linked immunosorbent assay. The correlation between plasma DDP4 and the rate of abdominal aortic aneurysm progression was analyzed by Pearson correlation and multiple linear regression. The predictive performance of plasma DDP4 on abdominal aortic aneurysm progression was analyzed by Logistic regression model and receiver operating characteristic (ROC) curve. Results The thickness of intracavitary thrombus (P=0.046) and the rate of abdominal aortic aneurysm progression (P<0.001) in the progression group were greater/faster than those in the the progression-free group,and the plasma level of DDP was significantly higher than that in the progression-free group (P<0.001). Multivariate Logistic regression analysis showed that plasma DDP4 level was an independent predictor of abdominal aortic aneurysm progression (P<0.05). Pearson correlation analysis showed that plasma DDP4 level was positively correlated with the rate of abdominal aortic aneurysm progression (r=0.517,P<0.001). After adjusting for other confounding factors,multiple linear regression showed that there was still a significantly positive correlation between plasma DDP4 level and abdominal aortic aneurysm progression rate (β=0.312,95％CI:0.002 to 0.484,P=0.048). The area under the curve of baseline plasma DDP4 level for predicting abdominal aortic aneurysm progression was 0.840 (95％CI:0.704 to 0.976),with corresponding cutoff value of 13.89 pg/mL,specificity of 85.7％,and sensitivity of 79.3％. Conclusion Elevated plasma DDP4 levels in patients with abdominal aortic aneurysm are associated with a higher risk of aneurysm progression. Plasma DDP4 is expected to be a predictive biomarker for abdominal aortic aneurysm progression.

Natural products are important sources for the discovery of anti-tumor drugs. Evodiamine is the main alkaloid component of the traditional Chinese herb Wu-Chu-Yu, and it has weak antitumor activity. In recent years, a number of highly active antitumor candidates have been discovered with a significant progress. This article reviews the research progress of evodiamine-based antitumor drug design strategies, in order to provide reference for the development of new drugs with natural products as leads.