Chronic mucocutaneous candidiasis (CMC) is an infectious phenotype characterized by recurrent or persistent infections caused by Candida species that affect the skin, nails, oral, and genital mucosae for a duration exceeding six months. Current research suggests that CMC is an immunodeficiency disease with a complex pathogenesis. Patients with CMC have various defects in nonspecific and/or specific immunity against Candida infection, resulting in the inability of patients to defend themselves against Candida infection. CMC can be stratified into primary CMC and secondary CMC based on etiology. Primary CMC is often associated with genetic mutations leading to immunodeficiencies in T helper cell 17 and interleukin-17, whereas secondary CMC is frequently linked to factors such as human immunodeficiency virus infection, diabetes mellitus, and immunosuppressive therapy. Primary CMC typically manifests as Candida infections, with distinct genetic mutations often correlating to varied concomitant symptoms. Secondary CMC may present with not only superficial mucosal Candida infections and manifestations of the underlying primary disease but also with invasive fungal infections. Diagnosing CMC requires an integration of medical history and clinical presentation, supplemented by the outcomes of auxiliary diagnostic procedures, including microscopic examination of fungal smear, fungal culture, immunological testing, and genetic sequencing and analysis. Furthermore, confirming primary CMC requires exclusion of the aforementioned secondary factors. At present, antifungal drugs such as triazoles, echinocandins, and polyenes are the main treatment for CMC. Moreover, immunotherapy with biologics such as Janus kinase (JAK) inhibitors provides more options for the clinical treatment of patients with CMC. Gene therapy also has potential clinical application value. In this review, we discuss the etiologies, pathogenesis, clinical manifestations, diagnosis, and treatments of CMC, aiming to provide a reference for the clinical diagnosis and treatment of CMC.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

[Objective] To retrospectively analyze the detection results of alanine aminotransferase (ALT) unqualified repeat blood donors in Guangzhou, so as to provide evidence for further expanding the repeat blood donor pool, reducing the rate of blood discarding and improving the qualified rate of blood test. [Methods] Blood donors with unqualified ALT in Guangzhou Blood Center from January 2018 to April 2024 were selected as the research objects. The past blood donation and population characteristics were analyzed according to the number of blood donations and ALT unqualified times. [Results] Among repeat blood donors with previous ALT disqualification, 99.5% to 99.7% did not have reactive markers for transfusion-transmitted diseases (TTD), which was higher than the rate among first-time blood donors with unqualified ALT (95.8%) (P<0.05). The rate of single-item ALT disqualification in repeat blood donors was higher in males than in females (P<0.05); it also varied by age (18-25 years > 26-35 years > 36-45 years > over 45 years) (P<0.05); and by quarter (third and fourth quarters > first and second quarters) (P<0.05). The ALT unqualified rate was significantly higher whole blood donors than that of platelet donors and returning blood donors (P<0.05). The overall ALT level (51.0 U/L), individual ALT level (56.0 U/L) and individual ALT unqualified rate (66.7%) of repeat blood donors with multiple ALT disqualifications were higher than those of repeat blood donors with single-item ALT disqualifications (26.0 U/L, 38.5 U/L, and 33.3%, respectively) (P<0.05). Moreover, as the number of ALT disqualifications increased, the overall level of ALT in repeat blood donors also increased (P<0.05), and the average level of individual ALT and individual ALT unqualified ratio tended to increase. Repeat blood donors with frequent ALT disqualifications had higher ALT levels (69.0 U/L). [Conclusion] The ALT unqualified rates of repeat blood donors were mostly non-specific elevation without TTD. Repeat blood donors with multiple ALT disqualifications tend to have continuous high ALT. Moreover, and with the increase of ALT disqualifications times, the overall ALT levels the average individual ALT levels and individual ALT unqualified rates showed an increasing trend.

OBJECTIVES: To investigate the therapeutic mechanism of 2,6-dimethoxy-1,4-benzoquinone (DMQ) for alleviating dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in mice. METHODS: Eighteen male C57BL/6J mice were equally randomized into control group, DSS group and DMQ treatment group. In DSS and DMQ groups, the mice were treated with DSS in drinking water to induce UC, and received intraperitoneal injections of sterile PBS or DMQ (20 mg/kg) during modeling. The changes in body weight, disease activity index (DAI), colon length, spleen weight, and colon histological scores of the mice were examined, and the percentages of Th17 and IFN-γ⁺ CD8⁺ T cells in the mesenteric lymph nodes and spleen were analyzed using flow cytometry. The expressions of tight junction proteins (Occludin and ZO-1), proteins associated with inflammasome activation (caspase-1 and p20), IL-1β and TNF-α in the colon tissues were detected using Western blotting or ELISA. In the cell experiment, mouse bone marrow-derived macrophages (BMDMs) primed with lipopolysaccharide (LPS) were treated with DMQ, followed by stmulation with nigericin to activate the classical NLRP3 inflammasome pathway. In cultured human peripheral blood mononuclear cells (PBMCs) treated with either LPS alone or LPS plus nigericin, the effects of DMQ on inflammasome activation, pyroptosis, and cytokine release were evaluated via Western blotting, ELISA, and flow cytometry. RESULTS: In DSS-treated mice, DMQ treatment significantly alleviated DSS-induced body weight loss, colon shortening, spleen enlargement, and colon inflammation. The DMQ-treated mice showed significantly reduced percentages of Th17 cells and IFN-γ⁺ CD8⁺ T cells in the mesenteric lymph nodes and spleen, with increased occludin and ZO-1 expressions and decreased caspase-1 expression in the colon tissue. DMQ obviously inhibited classical NLRP3 inflammasome activation in mouse BMDMs and both the classical and alternative pathways of NLRP3 activation in human PBMCs, causing also suppression of caspase-1-dependent pyroptosis. CONCLUSIONS DMQ ameliorates DSS-induced UC in mice by inhibiting NLRP3 inflammasome activation.
Animals ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Mice, Inbred C57BL ; Colitis, Ulcerative/metabolism* ; Dextran Sulfate/adverse effects* ; Male ; Inflammasomes/metabolism* ; Mice ; Benzoquinones/therapeutic use* ; Th17 Cells ; Caspase 1/metabolism*

OBJECTIVE: To describe a novel arthroscopic technique of modified tri-anchor double-pulley suture-bridge in repairing medium-sized supraspinatus tendon tears and evaluate the early effectiveness. METHODS: Between June 2021 and January 2024, 26 patients with medium-sized supraspinatus tendon tears who underwent arthroscopic modified tri-anchor double-pulley suture-bridge repair and met the selective criteria were included. There were 11 males and 15 females with an average age of 61.4 years (range, 43-74 years). Five patients had a significant history of trauma, while the remaining 21 patients had no apparent cause. The time from symptom onset to hospitalization was 3-25 months (mean, 7.9 months). The effectiveness was evaluated during follow-up, including the scores of University of California at Los Angeles (UCLA), American Shoulder and Elbow Surgeons (ASES), visual analogue scale (VAS), the range of forward flexion, abduction, external rotation, and internal rotation, and patient's satisfaction. Either MRI or ultrasound examination were used to evaluate structural integrity of the tendon. RESULTS: The operation time was 65-110 minutes (mean, 81.8 minutes). All patients were followed up 12-43 months (mean, 23.0 months). At 3 and 12 months after operation, the shoulder range of flexion, abduction, external rotation, and internal rotation, and the scores of VAS, UCLA, and ASES significantly improved when compared with those before operation ( P<0.05). The improvement was further observed at 12 months compared to 3 months ( P<0.05). At last follow-up, 13 patients were very satisfied with the effectiveness, 11 patients were satisfied, 1 was relatively satisfied, and 1 was dissatisfied. During follow-up, 15 patients underwent imaging examination and imaging reexamination showed that the re-tear rate of tendon was 6.6%(1/15). The remaining 11 patients refused imaging examination. Complications included partial anchor withdrawal in 1 case, shoulder stiffness in 5 cases, and mild pain in shoulder joint in 2 cases in physical activity or heavy physical activity. CONCLUSION Arthroscopic modified tri-anchor double-pulley suture-bridge technique is a novel surgical technique that uses double-loaded suture anchors as medial- and lateral-row anchors. In repairing medium-sized supraspinatus tendon tears, 6 sets of double-pulley suture-bridges can be created from one medial-row anchor; knotless medial-row can reduce re-tear rate of the tendon; good early effectiveness is obtained.
Humans ; Female ; Male ; Middle Aged ; Arthroscopy/methods* ; Adult ; Rotator Cuff Injuries/surgery* ; Aged ; Suture Techniques ; Treatment Outcome ; Suture Anchors ; Rotator Cuff/surgery* ; Range of Motion, Articular ; Tendon Injuries/surgery* ; Patient Satisfaction

BACKGROUND: Early control of low-density lipoprotein cholesterol (LDL-C) is crucial for reducing the progress of cardiovascular disease. However, its additional role to the risk of primary osteoporosis in men with coronary heart disease was inconclusive. Our study aims to determine the association of LDL-C and its trajectories for osteoporosis risk in the middle-aged and aged men of China. METHODS: The retrospective cohort study of 1546 men aged 69.74 ± 11.30 years conducted in Beijing, China from 2015 to 2022. And the incidence of primary osteoporosis was annually recorded. LDL-C trajectories were further identified by latent class growth model using repeated measurements of LDL-C. The association of baseline LDL-C for osteoporosis was estimated using hazard ratio (HR) with 95% CI in Cox proportional hazard model, while mean level and trajectories of LDL-C for osteoporosis were evaluated using odds ratio (OR) with 95% CI in logistic regression model. RESULTS: During the median 6.2-year follow-up period, 70 men developed primary osteoporosis. The higher level of baseline LDL-C (HR = 1.539, 95% CI: 1.012-2.342) and mean LDL-C (OR = 2.190, 95% CI: 1.443-3.324) were associated with higher risk of osteoporosis in men with coronary heart disease after adjusted for covariates. Compared with those in the LDL-C trajectory of low-stable decrease, participants with medium-fluctuant trajectory, whose longitudinal LDL-C started with a medium LDL-C level and appeared an increase and then decrease, were negatively associated with osteoporosis risk (OR = 2.451, 95% CI: 1.152-5.216). And participants with initially high LDL-C level and then a rapid decrease demonstrated a tendency towards reduced risk (OR = 0.718, 95% CI: 0.212-2.437). CONCLUSIONS Elevated LDL-C level and its long-term fluctuation may increase the risk of primary osteoporosis in men. Early controlling a stable level of LDL-C is also essential for bone health.