搜索结果：Image

Childbearing entails complex biopsychosocial challenges that have important implications for women's reproductive autonomy. Given that childbirth involves substantial bodily changes, body image concerns are increasingly relevant to understanding women's reproductive psychology and fertility decision-making. In particular, fear of childbirth has been associated with lower fertility intentions among young, nulliparous women. Grounded in objectification theory, the present research examined whether self-objectification (internalized body surveillance rooted in appearance-based concerns) was associated with fertility intentions through fear of childbirth. Two complementary studies were conducted with Chinese nulliparous women aged 18-48 years (total N = 908): a cross-sectional survey (Study 1; n = 666, Mage = 26.46, SD = 4.23) and a randomized experiment (Study 2; n = 242, Mage = 26.16, SD = 4.89). In Study 1, self-objectification, fear of childbirth, and fertility intentions were assessed using validated measures. In Study 2, participants were randomly assigned to view either an objectifying video (designed to induce self-objectification) or a neutral control video, followed by assessments of fear of childbirth and fertility intentions. Across both studies, higher self-objectification was associated with greater fear of childbirth and lower fertility intentions. Mediation analyses indicated that fear of childbirth indirectly linked self-objectification to fertility intentions. These findings help connect objectification theory with reproductive psychology by highlighting body-image-related correlates of childbirth-related concerns. These findings also point to the potential value of social and psychological supports that promote young nulliparous women's reproductive mental health and safeguard their reproductive autonomy.

Oral squamous cell carcinoma (OSCC) is often preceded by oral potentially malignant disorders (OPMDs). Despite this known association, the transition from an OPMD to OSCC is complex, unpredictable, and non-linear, making early detection and intervention challenging for clinicians. Histopathological grading, the current standard for risk stratification, is not reliably predictive of malignant transformation (MT), and is subject to significant inter- and intra-observer variability. This scoping review evaluates emerging evidence on the integration of artificial intelligence (AI) and machine learning (ML) with molecular and histopathologic biomarkers to enable individualized risk assessment for MT. Ten retrospective studies incorporating AI/ML algorithms were analyzed, utilizing biomarkers ranging from gene expression panels, biochemical and protein-based markers like S100A7 to image-derived histomorphometric features. These models demonstrated promising predictive accuracy, with histology-derived features showing the greatest clinical feasibility. However, variability in methodologies, lack of prospective validation, and inconsistent demographic reporting limit the generalizability of the findings. This review highlights the need for multimodal biomarker integration, prospective clinical trials, and validation across broader populations. Ultimately, AI/ML-enhanced tools hold significant potential to inform personalized surveillance and treatment decisions in OPMD, but their clinical readiness requires further refinement and robust validation.

Hepatocellular carcinoma (HCC) is a lethal cancer. Early recurrence, i.e., recurrence within two years of curative treatment, is a major determinant of ultimate survival. We included 625 patients with newly diagnosed early-stage HCC, i.e., Barcelona Clinic Liver Cancer (BCLC) Stage 0 or A, and Child-Pugh Class A liver disease who underwent percutaneous radiofrequency ablation (RFA) between 2011 and 2021 at our institution with a follow-up period of > 2 years. The patients were divided into Group 1 (patients who developed nonlocal recurrence or died within two years after RFA; n = 300 [48.0%]) and Group 2 (patients who developed local recurrence within two years or were recurrence-free and were alive for two years after RFA; n = 325 [52.0%]). Multivariate analysis showed that a Model for End-Stage Liver Disease (MELD) score of > 9, anti-hepatitis C virus (HCV) positivity, the presence of image-defined cirrhosis, treatment with antiviral therapies for hepatitis B virus or HCV, alpha-fetoprotein ≥ 20 ng/mL, multiple tumors, and larger tumor size were independent factors associated with Group 1. A nomogram was developed based on these variables to predict Group 1, with a concordance index of 68.3% (95% CI = 64.1%-72.5%). The 10-year overall survival of Group 1 was 28%, and that of Group 2 was 64%. We developed a nomogram to predict true early recurrence (i.e., nonlocal recurrence) of HCC after RFA.

Chlamydia psittaci pneumonia (CPP) is a rare but potentially severe zoonotic disease.This study aimed to characterize the computed tomography(CT)findings of CPP and evaluate the utility of CT severity scores for predicting intensive care unit(ICU) admission. We retrospectively analyzed patients diagnosed with CPP between January 2022 and September 2025.Patients were divided into ICU and non-ICU groups based on disease severity and ICU admission.Demographic, clinical, laboratory, and radiological data were collected.Two radiologists independently reviewed CT images to record imaging features and calculate two scores: the chest CT score(CTS, range 0-25 based on lobar involvement)and the chest CT severity score(CTSS, range 0-40 based on 20 lung segments).Multivariable logistic regression and receiver operating characteristic(ROC)curve analyses were performed to identify predictors of ICU admission.We further compared the predictive performance of CTS with that of the CURB - 65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) score, a widely - utilized clinical severity assessment tool for community - acquired pneumonia. The CURB - 65 score was calculated for each patient upon admission. A total of 69 patients were included(45 male,24 female; mean age 61.6 ± 12.5years).A history of poultry or bird exposure was reported in 65 patients(94.2%).The ICU group comprised 22 patients(31.9%).Among survivors(n = 65),follow-up showed complete clinical recovery, and repeat CT imaging demonstrated complete resolution or marked improvement of interstitial abnormalities in those with available follow-up scans, supporting the reversible acute nature of these changes.In the ICU group, both the CTS (9.9 ± 6.4 vs. 5.9 ± 3.4, P = 0.011) and CTSS (13.5 ± 9.0 vs. 9.0 ± 4.8, P = 0.035) were significantly elevated. ROC analysis indicated that the area under the curve was 0.710 for CTS (cut - off 7.5; sensitivity 63.6%; specificity 76.6%) and 0.657 for CTSS. The CURB - 65 score yielded an area under the curve (AUC) of 0.633 (95% confidence interval [CI]: 0.476-0.790, P = 0.076). The DeLong test showed no statistically significant difference between the AUCs of the CTS and CURB - 65 (P = 0.452). Notably, only the CTS reached statistical significance in predicting intensive care unit (ICU) admission, implying that computed tomography (CT) - based severity assessment might offer prognostic information that cannot be captured solely by clinical score. This study provides a detailed imaging characterization of CPP.CT severity scores, particularly the CTS, are independently associated with ICU admission and may serve as adjunctive tools for early risk stratification.The reversible nature of interstitial changes on follow-up supports their acute inflammatory origin.Compared with CURB-65,the CTS offered a numerically higher AUC and provided significant prognostic information where clinical scoring alone did not.

Adenosine rapidly suppresses antitumor immunity through the adenosine A2A receptor (A2AR). Immunogenic cell death (ICD) releases extracellular ATP, which can be rapidly converted into immunosuppressive adenosine. We therefore designed BSCS@PHY to synchronize ICD induction with local A2AR blockade in the same spatiotemporal window, aiming to protect antigen priming from adenosine-mediated suppression. BSCS@PHY integrates a bismuth-copper diselenide core for photothermal heating, glutathione depletion, and chemodynamic hydroxyl-radical generation; hyaluronic-acid-modified phase-change materials for on-site activation; the A2AR antagonist SCH442416 for local A2AR blockade; and yeast cell wall (YCW) components for innate adjuvanticity. Thermography-guided irradiation confines activation within a controlled window, melts the phase-change shell to expose the catalytic surface, and coordinates ICD amplification with co-localized A2AR blockade and dendritic-cell activation. In 4T1 tumors, BSCS@PHY enables image-guided activation, enhances ICD hallmarks, lowers adenosine signaling, promotes dendritic-cell maturation and T-cell priming, and improves tumor control, with additional benefit when combined with anti-PD-L1. Loss-of-function comparisons support nonredundant contributions of A2AR blockade and YCW-mediated adjuvanticity. This material-encoded strategy aligns danger-signal generation with local A2AR blockade in the same tumor niche and offers a framework for pairing ICD induction with metabolic-checkpoint control in cold tumors.

The Bonwill triangle, defined by the mandibular incisor (MI) point and the center of right (CR) and left (CL) condyles, which provide a crucial reference for determining craniofacial symmetry and occlusion. Although three-dimensional imaging has enhanced the precision of triangle measurement, few studies have evaluated Bonwill triangle geometry in patients who have undergone orthognathic surgery (OGS). The present study assessed Bonwill triangle geometry in a Taiwanese population by comparing individuals who underwent OGS and those who did not and by analyzing the effects of sex and age on mandibular asymmetry. Cone-beam computed tomography images from 109 adults (54 in the OGS group and 55 in the non-OGS group) were retrospectively analyzed. Three side lengths of the Bonwill triangle (mandibular incisor point to left condyle (MI-CL), mandibular incisor point to right condyle (MI-CR), and right condyle to left condyle (CR-CL)) were measured using Mimics software. Group comparisons and subgroup analyses by sex and age were conducted using independent and paired t tests and Pearson correlation analysis. The OGS group exhibited greater asymmetry in the bilateral side lengths than the non-OGS group did (3.41&#x2009;&#xb1;&#x2009;2.35&#xa0;mm vs. 1.69&#x2009;&#xb1;&#x2009;1.02&#xa0;mm, p&#x2009;<&#x2009;0.001), particularly the men in the group (p&#x2009;<&#x2009;0.001). Additionally, only the men in the OGS group exhibited a negative correlation between age and bilateral side length (r&#x2009;=&#x2009;-&#x2009;0.480, p&#x2009;=&#x2009;0.034). CR-CL length did not differ significantly between the OGS and non-OGS groups. The Bonwill triangle can support preoperative mandibular asymmetryassessments. Candidates for OGS, especially men, exhibit greater skeletal asymmetry than non-OGS candidates do, underscoring a need for individualized planning. Future studies evaluating surgical type and long-term outcomes can enhance the clinical applications of the Bonwill triangle in pre-OGS assessments. This retrospective study was approved by the Institutional Review Board of China Medical University Hospital, Taichung, Taiwan (CMUH 114REC2019).

Automated right ventricular (RV) analysis in 2D echocardiography is limited by the morphological complexity of RV segmentation and the domain fragility of single-center deep learning models across ultrasound vendors. No prior framework has jointly addressed both challenges for RV-specific segmentation. To develop and prospectively validate TACA-Net (Bi-Phase Adversarial Cross-Attention Network), a unified multi-center framework for simultaneous RV endocardial segmentation and three-class functional severity classification (normal, mildly reduced, significantly reduced) in 2D apical four-chamber echocardiography. Data were prospectively collected from three clinical sites within a single tertiary hospital network, each equipped with a different ultrasound vendor. Centers A and B (n = 1,240 patients) were used for training and 5-fold cross-validation; Center C (n = 320 patients) served as the fully held-out external test set. TACA-Net integrates a gradient reversal layer-based domain discriminator for vendor-agnostic feature learning, a bidirectional bi-phase cross-attention module encoding the complementary information between end-diastolic and end-systolic representations, and a dual-head decoder jointly optimizing segmentation and classification with an auxiliary bi-phase consistency loss. Performance was benchmarked against six segmentation baselines (U-Net, Attention U-Net, TransUNet, Swin-UNETR, nnU-Net, MACS) and five classification baselines (ResNet-50, EfficientNet-B4, ViT-B/16, segmentation-then-classify pipeline, MACS + head). Primary segmentation endpoints were Dice Similarity Coefficient (DSC) and Hausdorff Distance 95th percentile (HD95); primary classification endpoint was macro-averaged area under the receiver operating characteristic curve (AUC). On the external test set, TACA-Net achieved a DSC of 0.903 &#xb1; 0.013 and an HD95 of 7.1 &#xb1; 1.0&#xa0;mm for RV segmentation, and a macro-averaged AUC of 0.911 (95% CI: 0.885-0.937) for functional classification, statistically significantly superior to all six segmentation and five classification baselines (all p < 0.01). Ablation analyses demonstrated independent contributions of domain alignment (&#x394;DSC = -0.038 when removed), bi-phase cross-attention (&#x394;AUC = -0.032), and multi-task joint training (&#x394;DSC = -0.014). No significant differential performance was detected across diagnosis subgroups, sex, or image quality strata. GradientSHAP attribution maps revealed highest feature importance in the RV lateral free wall, consistent with established RV pathophysiology. Expected calibration error for TACA-Net was 0.041 on the external test set, the lowest among all classification models evaluated. TACA-Net achieves vendor-agnostic RV segmentation and functional classification from routinely acquired 2D echocardiography, with robust multi-vendor generalization demonstrated under rigorous prospective external validation. The framework provides a clinically interpretable and methodologically transparent foundation for AI-assisted right heart assessment at scale.

Stratified binary supraparticles enable functional architectures for applications such as photonics, pharmaceutics, and additive manufacturing. However, the extent of stratification under predefined particle size ratios and compositions remains unclear. Here, stratification in spray-dried supraparticles from charge-stabilised binary mixtures of colloidal primary particles under such boundary conditions is quantified via SEM image analysis and confocal microscopy. These experiments reveal the existence of optimal combinations of size ratios and volume fractions that produce maximal stratification, contrasting the intuitive picture that stratification increases with increasing size ratios. For low volume fractions of small particles, stratification is maximal with size ratios of &#x223c;3-5 and shifts to lower size ratios with increasing relative volume fractions. CFD-DEM simulations reproduce this trend and provide a contour plot of the extent of stratification as a function of particle size ratio and volume fraction. The simulations further suggest that stratification is driven by migration of small particles through interstitial channels between large particles at lower small particle concentrations, while colloidal diffusiophoresis becomes prominent at higher small particle contents. The understanding of stratification under experimental boundary conditions provides a framework for the predictive design of hierarchical supraparticle architectures with tailored internal structure.

Imaging modalities play a critical role in determining surgical versus conservative management for distal radius fractures. This study aimed to evaluate the impact of two-dimensional (2D) and three-dimensional (3D) computed tomography (CT) on the decision to operate in distal radius fractures and to compare their influence between AO Type B and Type C fractures. This cross-sectional, survey-based study included 97 orthopedic and traumatology specialists. Twelve distal radius fracture cases classified according to the AO system (six Type B and six Type C) were selected. Participants were sequentially presented with plain radiographs, post-reduction radiographs in cast, 2D CT images, and 3D CT reconstructions for each case. After each imaging stage, participants were asked to indicate their decision to operate (surgical or conservative). Changes in the decision to operate were statistically analyzed. Among AO Type B fractures, the addition of CT imaging to plain and post-reduction radiographs did not significantly change the decision to operate in most cases (p&#x2009;>&#x2009;0.05). In contrast, among AO Type C fractures, the addition of 2D CT imaging significantly changed the decision to operate in favor of surgical management (p&#x2009;<&#x2009;0.05), whereas the subsequent addition of 3D CT did not produce a further significant change (p&#x2009;>&#x2009;0.05). For AO Type B distal radius fractures, the addition of CT imaging to plain and post-reduction radiographs had limited impact on the decision to operate. In AO Type C fractures, 2D CT imaging significantly influenced the decision to operate, whereas the subsequent addition of 3D CT did not provide an additional impact on the decision to operate. Descriptive survey study.

Colorectal cancer is one of the most prevalent malignant tumors worldwide. Early screening relies on accurate polyp detection during colonoscopy. Polyps in colonoscopic images exhibit diverse morphologies, indistinct boundaries, and low contrast. Specular reflections, fold occlusions, and imaging artifacts further complicate detection, which fail to meet the requirements of real-time clinical assistance. To address these challenges, we propose BCP-YOLO (You Only Look Once), a high-precision, relatively lightweight polyp detection framework built upon an improved YOLOv8 architecture, designed to achieve a well-balanced trade-off between detection accuracy and computational efficiency. First, to mitigate complex background interference and improve small polyp detection, a BiFormer module is integrated into the backbone network to enhance focus on salient polyp regions while suppressing noise. To alleviate boundary ambiguity, the CARAFE content-aware upsampling operator is incorporated into the feature fusion stage, to refine lesion boundaries and spatial details. PConv module is employed to optimize network efficiency, reducing computational cost while maintaining detection performance. Experimental results on the Kvasir-SEG and CVC-ClinicDB datasets demonstrate that BCP-YOLO achieves a mean average precision (mAP0.5) of 88.5% on Kvasir-SEG, representing a 3.4% improvement over the YOLOv8 baseline. Precision and recall increase by 5.5% and 1.3%, respectively. The model contains 11.7&#x2009;M parameters and achieves an inference speed of 104.1 frames per second (FPS). Five-fold cross-validation on both datasets validates its strong generalization capability and robustness. The method provides a high-accuracy and deployable solution for computer-aided diagnosis in real-time colonoscopy, offering significant potential to improve the reliability and efficiency of early colorectal cancer screening.

Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) co-occur frequently, and growing evidence, including neuropathology, supports synergistic interplay between the diseases. We tested whether a single T1-weighted MRI scan may differentiate neuropathologically confirmed comorbid AD/DLB and AD controls using heterogeneously acquired neuroimaging. We obtained structural neuroimaging, on two groups, AD with and without DLB pathology. Convolutional neural networks are trained across dimensions. We introduce a triple-ensemble strategy consisting of majority voting schemes within a variety of plane permutations. In addition, we conduct voxel-wise statistical analyses. Here we show convolutional neural networks record a classification accuracy of 0.820 and an f1 score of 0.79 in identifying comorbid DLB/AD from AD patients. Prediction accuracy is higher proximal to date of death, while the trained model largely outperforms clinical baseline diagnosis. The slice-level performance varies depending on the sampled brain location, with sensitivity highest in the temporal lobe and specificity highest in the occipital lobe. In DLB/AD, gray matter is relatively preserved though atrophy is observed in the occipital lobe, suggesting that the comorbidity differentially affects brain loss and may accelerate it in the occipital lobe. This study demonstrates how machine learning approaches can address diverse neuroimaging data from clinical sources to differentiate neurodegenerative diseases using a true gold standard of neuropathological confirmation. The frameworks utilized here can be extended to other diseases that are frequently co-occurring and feasibly extend to single scan diagnostic clinical utility of scans already being acquired. Alzheimer&#x2019;s disease (AD) and lewy body dementia (LBD) are both progressive neurodegenerative diseases that result in declines in memory and other cognitive functions. AD and LBD are known to occur together, however conventional methods that image the brain are unable to accurately show the effect of these diseases. Specialized computational methods may be able to more accurately diagnose these conditions than clinical evaluation. We used brain imaging data that is commonly obtained to see whether we could identify people with suspected AD who also had LBD. Our method identified the places in the brain whether both AD and LBD are likely to occur and was able to better diagnose in patients with confirmed disease at death that usual clinical diagnosis methods. Our method could be used to better identify people with AD and LBD and thus allow earlier appropriate treatment.

To develop a method for accurate identification and localization of facial acupoints based on geometric and topological relationships (GTRs) among facial key points and organ features. A facial acupoint localization framework was constructed using the Google MediaPipe machine learning toolkit to extract 478 facial key points. Geometric and topological relationships between predefined acupoints and key facial landmarks were established. Based on these relationships, a rule-based mapping algorithm was designed to identify and localize facial acupoints. The method was applied to facial images collected from individuals undergoing acupuncture and physical therapy, and its localization performance was evaluated. The proposed method successfully identified and localized facial acupoints based on stable geometric and topological relationships. The approach demonstrated consistent performance across different facial structures, enabling accurate positioning of acupoints without the need for large-scale annotated datasets. The results indicate that the method is feasible and reliable for practical applications. The GTR-based approach provides an effective and efficient solution for facial acupoint identification and localization, reducing dependence on manual annotation and improving applicability in clinical and intelligent acupuncture systems.

The goal of developing interventions to slow ageing is not only lifespan extension but more importantly to increase healthspan, the period of life spent in active good health. Nutritional interventions have emerged as a potential strategy to maintain health with age. Testing these interventions for effects on human ageing would take several years and require large cohort sizes. We therefore employed C. elegans&#xa0;as a rapidly ageing model organism to investigate the effects of two commercially available nutrition-based products on ageing-related decline of mobility as an indication of healthspan. These products are multi-ingredient formulations comprising vitamins, minerals, antioxidants, amino acids and botanical extracts. They include compounds expected to positively influence ageing such as Dihydronicotinamide mononucleotide, NAD&#x2009;+&#x2009;booster, trans-resveratrol, taurine, pterostilbene and bioflavonoids. V14&#x2122; contains 40&#x2009;+&#x2009;ingredients and AG1&#xae; contains 70&#x2009;+&#x2009;ingredients with 5 additional probiotic strains. Mobility-based readouts over time were obtained using WormGazer&#x2122; imaging technology. Worms exposed to V14&#x2122; showed increased movement and speed with age compared to those exposed to AG1&#xae; and to a solvent control. To investigate the underlying mechanisms, transcriptomic profiling was performed on V14&#x2122; exposed worms, revealing modulation of pathways involved in metabolism and stress responses, processes associated with ageing. Collectively, these findings suggest that V14&#x2122; delays age-related decline in C. elegans&#xa0;and highlight the potential of targeted nutritional interventions to modulate pathways relevant to human ageing.

Acute myeloid leukemia (AML) remains a therapeutic challenge due to drug resistance and relapse, which are often driven by the protective bone marrow (BM) niche. Conventional xenograft models fail to adequately recapitulate this niche-specific pathophysiology. To overcome this limitation, a novel magnetically targeted intramedullary (MagIC-TI) xenograft model was developed. Magnetically labeled doxorubicin (DOX)-resistant HL60 cells (Mag-Re) were injected into the femurs of NSG (nonobese diabetic [NOD] Cg-PrkdcscidIL2rgtm1Wjl/SzJ) mice using a patented microinjection syringe under localized magnetic guidance. With the MagIC-TI model, rapid (day 1) and specific (100% by day 7) leukemic engraftment was achieved within the femoral BM, whereas intravenous (IV) injection led to delayed (mean 23.67&#x2009;&#xb1;&#x2009;10.26 days) and disseminated engraftment. Bioluminescence imaging, histopathological analysis, flow cytometry, and molecular assays confirmed that disease was localized in the MagIC-TI model. In contrast, extramedullary infiltration, predominantly in the lungs, spleen, liver, and kidneys, was observed early in progression in the IV model. The MagIC-TI model discriminated drug responses, showing effective tumor burden reduction with homoharringtonine (HHT) and unequivocal DOX resistance, a distinction that was obscured in heterogeneous IV models. Furthermore, employing a semisolid decalcification (SSD) system preserved green fluorescent protein (GFP) fluorescence, enabling high-resolution visualization of engrafted cells within bone tissue. The MagIC-TI model enables BM-targeted, rapid, and efficient leukemic engraftment and allows discrimination of drug sensitivity and resistance. This model provides a robust and reproducible platform for modeling the leukemia BM niche and for preclinical evaluation of niche-directed therapies.

BACKGROUND Traumatic intrusion of permanent incisors is one of the most severe forms of dental injury and is frequently associated with complications such as pulp necrosis, root resorption, and ankylosis. Although IADT guidelines provide structured recommendations based on the stage of root development and degree of intrusion, some clinical situations remain borderline, particularly cases presenting an open apex in an otherwise nearly mature root, making classification and treatment planning challenging. CASE REPORT A 7-year-old girl presented with severe intrusive luxation (>10 mm) of the permanent right maxillary central incisor. Clinical and radiographic assessment revealed a wide apical foramen but near-complete root length, placing the case in a borderline category. A multidisciplinary plan was initiated, consisting of surgical repositioning and flexible splinting, followed by orthodontic extrusion. After 2 months of traction, undesirable intrusion of the adjacent incisors occurred, while the affected tooth failed to extrude, raising suspicion of ankylosis and leading to suspension of active orthodontic forces. Due to concurrent maxillary constriction, rapid palatal expansion was performed. Unexpectedly, spontaneous re-eruption of the intruded incisor occurred shortly after completing expansion, without further orthodontic intervention. CONCLUSIONS This case illustrates borderline presentations can require adaptive and individualized treatment strategies beyond standard guideline recommendations. The spontaneous re-eruption observed after expansion suggests orthopedic interventions modify local conditions, potentially facilitating natural repositioning, even in teeth initially suspected of ankylosis. Nevertheless, the relationship between expansion and eruptive recovery should be interpreted as hypothetical rather than causative. Further clinical reports are needed to elucidate the biological mechanisms underlying this phenomenon and define its potential therapeutic relevance.

Anterior cruciate ligament (ACL) injuries are frequently associated with meniscal tears. MRI diagnostic performance varies by tear pattern and location and may be influenced by imaging timing and reader variability. This study evaluated pattern-specific MRI accuracy compared with arthroscopic findings and assessed the impact of timing and inter-reader reliability. This retrospective study included consecutive patients undergoing ACL reconstruction with confirmed complete ACL tears and available preoperative MRI. Meniscal tears were classified as horizontal, vertical, radial, complex, and bucket-handle. Arthroscopy served as the reference standard. Diagnostic metrics, inter-reader agreement (&#x3ba;), and time intervals between injury, MRI, and surgery were analyzed. A total of 143 patients were included. Medial meniscal tears were present in 81 patients (56.6%) and lateral tears in 69 (48.3%). MRI accuracy was 71.3% for medial tears (sensitivity 86.4%, specificity 51.6%) and 72.0% for lateral tears (sensitivity 88.4%, specificity 56.8%). Bucket handle tear patterns showed the highest inter-reader reliability (&#x3ba;&#x2009;=&#x2009;0.78), while radial tears demonstrated the lowest inter-reader reliability (&#x3ba;&#x2009;=&#x2009;0.16). In adjusted analyses, neither meniscal location nor any injury-MRI, MRI-surgery, or injury-surgery interval was significantly associated with diagnostic performance (all p&#x2009;&#x2265;&#x2009;0.38). MRI shows moderate accuracy and fair-to-substantial reliability for meniscal tears in ACL-deficient knees, with the best performance in bucket-handle tear patterns. The greatest inter-reader variability was observed for radial tears. Although no significant association between timing intervals and diagnostic performance was identified, timing-related findings should be interpreted cautiously because of potential measurement error and the retrospective design. The study registration was not performed due to the retrospective design.

Spontaneous regression of colorectal liver metastasis (CRLM) is an extremely rare phenomenon with only a few reported cases. However, the underlying mechanism remains unclear. Infection-triggered immune reactivation and inflammation have also been proposed to be potential contributors. IgG4-related disease (IgG4-RD) is a systemic fibroinflammatory condition characterized by IgG4-positive plasma cell infiltration and fibrosis, and rarely manifests in the liver as an inflammatory pseudotumor (IPT). We herein report a rare case of a 71-year-old man with possible spontaneous regression of CRLM accompanied by coexisting IgG4-rich IPT-like changes. Eight months after the laparoscopic Hartmann's operation for rectal cancer, imaging revealed hepatic lesions in segments S5 and S7, which were diagnosed as CRLM. Partial hepatectomy revealed necrotic adenocarcinoma in the S7 lesion, with IgG4-rich IPT-like inflammatory changes. Postoperative evaluation revealed markedly elevated serum IgG4 levels and IgG4-positive plasma cell infiltration in the mediastinal lymph nodes, fulfilling the diagnostic criteria for systemic IgG4-RD. Twenty months postoperatively, the patient remained recurrence-free without adjuvant chemotherapy or steroid therapy. This case report describes the coexistence of spontaneous tumor regression and IgG4-related hepatic IPT within the same lesion and provides insight into the clinicopathological spectrum linking tumor regression and IgG4-RD.

Cerebral small vessel disease (CSVD) is a leading cause of vascular cognitive impairment, yet its earliest stages remain clinically silent and poorly detected. Although white matter hyperintensities (WMHs) are widely used neuroimaging markers, conventional cardiovascular risk scores and cognitive testing lack sensitivity to subclinical cerebrovascular injury. This study investigated whether circulating microparticles (MPs) and fractal analysis of the Circle of Willis (CoW), reflecting cerebrovascular network-hemodynamic complexity, could provide an early, mechanistically informative marker of silent CSVD. Sixty asymptomatic adults with low-to-moderate cardio-cerebrovascular risk (QRISK3) underwent 3&#x2009;T MRI, cognitive testing, and circulating MPs profiling. Cerebrovascular fractal dimension of the CoW (Df [W]) was computed from 3D time-of-flight magnetic resonance angiography. Multivariable regression, mediation analysis (10,000 bootstraps), and ROC analyses were performed. Reduced Df (W) was strongly associated with greater WMHs burden (p&#x2009;<&#x2009;0.001) and significantly outperformed QRISK3 and MPs in discriminating WMHs (AUC&#x2009;=&#x2009;0.928 vs. ~0.75). Leukocyte-derived (CD62L+) and platelet-derived (CD62P+) MPs were elevated in participants with WMHs and correlated with both WMHs burden and Df (W), but lost independent significance after adjustment for WMHs, indicating upstream systemic vascular injury. Mediation analysis confirmed that MPs influenced WMHs' burden primarily through their effect on cerebrovascular Df (W). A combined biological-imaging model integrating MPs and Df (W) achieved near-perfect diagnostic accuracy (AUC&#x2009;=&#x2009;0.952). Despite marked vascular and microstructural abnormalities, neurocognitive performance was preserved, with only a weak association between processing speed and Df (W), consistent with network reserve in early CSVD. Thus, cerebrovascular fractal complexity may capture the structural imprint of cumulative vascular injury and enable biologically grounded detection of preclinical CSVD.

Retinal organoids represent a promising regenerative strategy for restoring vision in retinal degenerative diseases, but the capacity of host cone bipolar cells in the primate macula to rewire with transplanted photoreceptors has not been established. In this study, we transplanted genome-edited ISL1-/- human retinal organoids lacking ON-bipolar cells into an acute laser-induced macular photoreceptor ablation nonhuman primate model. Using immunohistochemistry, ultrastructural imaging, and focal macular electroretinography (FMERG), we demonstrate that host rod and cone bipolar cells actively extend dendrites toward grafted photoreceptors and form synaptic contacts, with evidence of functional signal transmission in a subset of transplanted eyes. Longitudinal, per-eye analyses revealed that host ON-bipolar responses improved in two of four eyes with ISL1-/- graft by up to 21.6% and remained stable for up to 2 years post-transplantation. Moreover, OFF-pathway connectivity showed potential progressive maturation, with delayed increase in d-wave after 13 months in one of those eyes. These findings provide the first demonstration of long-term anatomical host-graft synaptic integration in the primate macula, establishing that central cone bipolar circuits retain the capacity for durable rewiring with human stem cell-derived grafts. Our results highlight ISL1-/- retinal organoids as a promising approach for central vision restoration in macular degeneration.