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.

Hypercholesterolemia is pathologically characterized by abnormal accumulation of low-density lipoprotein cholesterol,which is closely associated with metabolic dysfunction-associated fatty liver disease and increased cardiovascular risks.Hepatocytes maintain cholesterol homeostasis through LDL receptor-mediated uptake and esterification storage mechanisms.However,chronic cholesterol overload induces mitochondrial dysfunction,reactive oxygen species accumulation,and endoplasmic reticulum stress,leading to hepatocyte injury.Moreover,systemic hypercholesterolemia disrupts gut microbiota balance and impairs short-chain fatty acid and ketone metabolism,exacerbating metabolic disturbances and aggravating hepatic injury through enhanced metabolic stress.In this article,we review the advance of studies on hypercholesterolemia in recent years and summary its association with hepatic injury,which can provide theoretical support for further research.

Hypercholesterolemia is pathologically characterized by abnormal accumulation of low-density lipoprotein cholesterol,which is closely associated with metabolic dysfunction-associated fatty liver disease and increased cardiovascular risks.Hepatocytes maintain cholesterol homeostasis through LDL receptor-mediated uptake and esterification storage mechanisms.However,chronic cholesterol overload induces mitochondrial dysfunction,reactive oxygen species accumulation,and endoplasmic reticulum stress,leading to hepatocyte injury.Moreover,systemic hypercholesterolemia disrupts gut microbiota balance and impairs short-chain fatty acid and ketone metabolism,exacerbating metabolic disturbances and aggravating hepatic injury through enhanced metabolic stress.In this article,we review the advance of studies on hypercholesterolemia in recent years and summary its association with hepatic injury,which can provide theoretical support for further research.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

Objective To evaluate the changes in postoperative plasma β-endorphin(β-EP)levels in patients who had received perioperative electroacupuncture(EA)treatment in 10 randomized controlled trials(RCTs)and examine the impact of EA on postoperative pain.Methods This meta-analysis evaluated the changes in plasma β-EP levels and visual analog scale(VAS)12,24 and 48 hours after surgery in patients receiving perioperative EA.It also assessed the changes in plasma serotonin(5-hydroxytryptamine,5-HT)and prostaglandin E2(PGE2)levels at 24 hours postsurgery.A comprehensive search was conducted in the China National Knowledge Infrastructure(CNKI),Wanfang,Chongqing VIP database,Chinese Biomedical Database(CBM),Web of Science,and PubMed databases.RCTs on perioperative EA and β-EP published from the inception of the websites up to July 25,2023,were retrieved.Effect size aggregation,literature quality assessment,and bias analysis were performed using RevMan 5.3 software,and sensitivity analysis was conducted via R 4.3.1.Results A total of 10 RCTs involving 706 patients were included.EA in conjunction with conventional anesthesia significantly increased plasma β-EP levels at 12 hours postsurgery[standard mean difference(SMD)=2.79,95%CI(1.85,3.72),Z=5.81,P＜0.00001],24hours postsurgery[SMD=1.87,95%CI(0.9,2.83),Z=3.79,P=0.0001],and 48 hours postsurgery[SMD=2.02,95%CI(1.49,2.54),Z=7.50,P＜0.00001].EA reduced plasma PGE2 levels at 24 hours postsurgery and plasma 5-HT levels at 24 hours postsurgery,and the VAS at 12,24 and 48 hours after surgery also decreased.Conclusion These findings suggest that perioperative EA markedly elevates plasma β-EP levels,reduces pain-inducing factors in plasma,and effectively alleviates acute postoperative pain.

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

Objective:To analyze the main active components and potential molecular mechanism of Yishen Tongluo Prescrip-tion(YTP)in the treatment of male infertility based on network pharmacological technology.Methods:We searched and sorted the main active components of YTP and their individual potential targets in the databases of Systematic Pharmacology of Traditional Chinese Medicine(TCM)and Bioinformatics Analysis Tool of the Molecular Mechanism of TCM,and screened the targets related to male infer-tility diseases in the databases of Genecards,DisGeNET and OMIM.We made a Venn diagram by intersecting the predicted targets of YTP and those of male infertility diseases,constructed visualized networks for the association of the intersection targets and protein-pro-tein interaction(PPI)using the Cytoscape software and STRING platform respectively,and conducted gene ontology(GO)and KEGG enrichment analyses using the DAVID database and R language"Cluster Profiler"software package respectively.Results:A total of 99 active components,250 targets of YTP,4 397 targets of male infertility and 127 common targets were identified.GO analysis re-vealed that the biological processes of the common targets mainly included transcriptional regulation of RNA polymerase promoter Ⅱ,regulation of gene expressions,regulation of apoptosis,responses to estrogen,and cell responses to hypoxia.KEGG analysis showed significant enrichment of the common targets in the estrogen signaling pathway,cell apoptosis pathway,AGE-RAGE signaling pathway in diabetic complications,and TNF signaling pathway.Conclusion:Through network pharmacology,we identified the main active components of YTP and its multi-target and multi-pathway mechanism in the treatment of male infertility,which has paved the ground for animal and cell experiments in verifying the action mechanism of YTP on male infertility.

Objective:To evaluate the efficacy and safety of traditional Chinese medicine(TCM)in the treatment of male im-mune infertility(MII)by meta-analysis.Methods:We retrieved randomized controlled trial(RCT)on the treatment of male im-mune infertility with traditional Chinese medicine from the databases of WanFang,Chinese Biomedical Literature,Cochrane Library,Weipu,PubMed and CNKI,and performed methodological quality assessment of the RCTs identified and statistical analysis and evalua-tion of the publication bias using the RevMan5.4 software.Results:Totally,25 RCTs(2 563 cases)were included in this study.Compared with Western medicine alone in the treatment of MII,TCM achieved a significantly higher total effectiveness rate(OR=6.35,95% CI:4.96-8.13,P<0.000 01),negative conversion rate of seminal plasma anti-sperm antibodies(OR=4.52,95% CI:2.72-7.51,P<0.000 01),negative rate of serum anti-sperm antibodies(OR=2.98,95% CI:2.23-3.96,P<0.000 01),sperm concentration(MD=15.56,95% CI:11.32-19.79,P<0.000 01),grade a sperm motility(MD=3.85,95% CI:1.91-5.79,P=0.000 01),grade a+b sperm motility(MD=13.77,95% CI:7.06-20.48,P<0.000 1),sperm viability(MD=10.32,95% CI:6.78-13.86,P<0.000 01)and pregnancy rate(OR=3.53,95% CI:2.68-4.63,P<0.000 01),but a lower rate of adverse reactions(OR=0.06,95% CI:0.01-0.23,P<0.000 01).There was no statistically significant difference in the percentage of morphologically abnormal sperm between TCM and Western medicine alone in the treatment of MII(MD=-7.53,95% CI:-15.50-0.44,P=0.06).Conclusion:TCM has a definite effectiveness and high safe in the treatment of male immune infertility.