ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective: To investigate the correlation between color parameters (L^*, a^*, b^*, Eab^*) and the contents of reducing sugars, total polysaccharides, total oligosaccharides, as well as four saccharides (fructose, glucose, sucrose, and kestose) during the nine cycles of steaming and sun-drying processing of Polygonatum kingianum, and to preliminarily explore the optimal processing duration.
Methods: The color changes were objectively evaluated using a colorimeter. The anthrone-sulfuric acid method was employed to determine total polysaccharides and oligosaccharides. The 3,5-dinitrosalicylic acid (DNS) colorimetric method was used to measure total reducing sugar content. High-performance liquid chromatography coupled with charged aerosol detection (HPLC-CAD) was applied for quantitative analysis of fructose, glucose, sucrose, and kestose. Multivariate statistical analysis was conducted to assess samples from different processing stages.
Results: Significant variations in color and component contents were observed across processing stages. The herbal pieces progressively darkened with increased processing cycles: brightness (L^*) and total color difference (Eab^*) initially decreased then stabilized, while a^* (red-green) and b^* (yellow-blue) values first increased then declined. Total polysaccharides and oligosaccharides showed overall decreasing trends, whereas reducing sugars initially increased before stabilizing. Fructose and glucose levels rose continuously, while sucrose and kestose decreased progressively, becoming undetectable after five cycles.
Conclusion: The chromatic alteration and saccharide composition of P. kingianum showed significant correlation with processing duration. Both total color difference (Eab^*) and reducing sugar content stabilized after four processing cycles (12 hours), suggesting that four cycles of steaming and sun-drying may represent the optimal processing duration.

Objective: To investigate the correlation between the color parameters (L^*, a^*, b^*, Eab^* values) of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucopyranoside, emodin, physcion, emodin-8-O-β-D-glucopyranoside, physcion-8-O-β-D-glucopyranoside.
Methods: The L^*, a^*, b^* and Eab^* values of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques were determined by spectrophotometer, and the contents of the five components were determined by high performance liquid chromatography. Secondly, SPSS 26.0 software and Simca 14.1 software were used to analyze the correlation.
Results: Through the hierarchical cluster analysis (HCA), it was found that the steamed samples and black bean steamed samples could be obviously divided into two categories: raw products and processed products. The processed products could be further divided into 2-8 h and 12-48 h. Pearson correlation analysis showed that the content of stilbene glycoside was significantly positively correlated with L^*, a^* and b^* values (P<0.01). The a^* value was significantly positively correlated with the content of emodin and physcion (P<0.01). Emodin-8-O-β-D-glucoside was positively correlated with L^* value and b^* value, while physcion-8-O-β-D-glucoside was negatively correlated with a^* value. Partial least squares discriminant analysis (PLS) showed that 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucoside (VIP=1.69) and emodin-8-O-β-D-glucoside (VIP=1.06) were the key variables affecting chromaticity characteristics (P<0.01).
Conclusion: The three processes of steaming, black bean steaming and black bean stewing are consistent in composition transformation and chromaticity variation, and stilbene glycoside can be used as a specific index component to characterize the processed color. Chromatic parameters can effectively reflect the processing progression and serve as quality monitoring indicators during production.

Objective To explore the clinical value of preoperative assessment and intraoperative frozen section pathology in screening patients suitable for testicular preservation surgery, so as to provide reference for reducing unnecessary radical orchiectomy in patients with benign testicular tumors. Methods A retrospective analysis was conducted on 121 patients who underwent surgical treatment for testicular tumors in the First Affiliated Hospital of Xi'an Jiaotong University during Jan. 2021 and Sep. 2025. Data were collected, including demographic information, preoperative imaging, serum tumor markers, surgical procedures, intraoperative frozen section, postoperative pathology, and postoperative testicular volume changes. Results Among the 121 patients, 105 underwent radical orchiectomy, with 91 malignant and 14 benign cases confirmed by postoperative pathology; 16 received testicular tumor enucleation, all confirmed as benign. Benign lesions accounted for 24.79% (30/121) of all cases. In patients undergoing tumor enucleation, intraoperative frozen section results were fully consistent with final pathological findings. Conclusion Preoperative differentiation between benign and malignant testicular tumors is crucial for selecting the appropriate surgical approach. For patients with preoperative findings suggesting benign lesions, testicular tumor enucleation combined with intraoperative frozen section can achieve precise treatment while maximizing testicular preservation.

Hepatic ischemia-reperfusion injury (HIRI) has been considered as an inevitable process of liver transplantation. Hepatocyte ferroptosis is a key factor in HIRI development, yet precise mechanism and potential therapies are still unclear. Here, we demonstrated a strong correlation between hepatocyte ferroptosis and the downregulation of poly(rC)-binding protein (PCBP2), which compromised the stability of antiporter system Xc^- (consisted of SL3A2/SLC7A11). Besides, inhibiting PCBP2 contributed to facilitating cofactor p300 to enhance the transcriptional activity of HIF1α, leading to the expression and secretion of HMGB1. Then, released HMGB1 from ferroptotic hepatocytes worsened M1 macrophage recruitment and immune response during HIRI. Additionally, acteoside (ACT) was shown to assist PCBP2 in stabilizing the mRNA stability of Slc3a2 and Slc7a11, as well as enhance the binding affinity of PCBP2-system Xc^-. Beyond that, ACT also supported PCBP2 to limit HMGB1-induced M1 macrophage recruitment through imposing restrictions on p300 and HIF1α. Furthermore, specific knockdown of PCBP2 in hepatocytes directly interposed the therapeutic efficacy of ACT on HIRI mice. In conclusion, ACT alleviated hepatocyte ferroptosis and HIRI via promoting PCBP2 to maintain the stability of system Xc^- and limit HIF1α/p300-HMGB1 signaling. These findings highlight the therapeutic benefits of ACT in treating HIRI and offer insights into innovative therapeutic strategies.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

The patient, assigned female at birth and aged 1 year and 7 months, presented with clinical manifestations of 46,XY disorders of sex development. The external genitalia exhibited a severely undermasculinized phenotype. Laboratory tests and gonadal biopsy indicated poor Leydig cell function and good Sertoli cell function. Genetic testing revealed compound heterozygous mutations of c.867-2A>C and c.547G>A (p.G183R) in the LHCGR gene. The patient was ultimately diagnosed with type II Leydig cell hypoplasia. Type II Leydig cell hypoplasia presents a broad spectrum of clinical phenotypes, characterized by a lack of parallel function between Leydig cells and Sertoli cells, and significant individual variability in spermatogenesis and gender assignment. This condition should be considered when there is poor Leydig cell function but good development of Wolffian duct derivatives.
Female ; Humans ; Infant ; Disorder of Sex Development, 46,XY/genetics* ; Leydig Cells/pathology* ; Mutation ; Receptors, LH/genetics* ; Testis/abnormalities*

OBJECTIVE: To investigate the relationship between serum levels of fibroblast growth factor-23 (FGF-23), heparanase (HPSE) and early renal impairment (RI) in patients with multiple myeloma (MM). METHODS: A retrospective analysis was conducted on the clinical data of 125 MM patients who were initially diagnosed in the Department of Hematology of the First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology from June 2020 to June 2023. The patients were divided into RI group (>176.80 μmol/L) and non-RI group (≤176.80 μmol/L) based on their serum creatinine levels when diagnosed. The baseline data and laboratory indexes of the two groups were compared. The relationship between serum FGF-23, HPSE and early RI in MM patients was analyzed. RESULTS: Among 125 newly diagnosed MM patients, 33 cases developed early RI, accounting for 26.40%. The proportion of light chain type, blood urea nitrogen (BUN), blood uric acid, lactate dehydrogenase, FGF-23, and HPSE levels in RI group were higher than those in non-RI group (all P <0.05). There was no statistical significant difference in other data between the two groups (P >0.05). Multivariate logistic regression analysis showed that BUN, FGF-23 and HPSE were associated with early RI in MM patients (all P <0.05). The serum FGF-23 level was divided into Q1-Q4 groups by quartile, and the serum HPSE level was divided into q1-q4 groups. The correlation analysis showed that with the increase of serum FGF-23 and HPSE levels, the incidence of early RI increased (r =0.668, 0.592). Furthermore, logistic regression analysis showed that after controlling for confounding factors, elevated levels of serum FGF-23 and HPSE were still influencing factors for early RI in MM patients (OR>1, P <0.05). According to Pearson's linear correlation test, there was a positive correlation between serum FGF-23 level and HPSE level (r =0.373). CONCLUSION There is a certain correlation between serum levels of FGF-23, HPSE and early RI in MM patients, and the incidence of early RI is higher in patients with abnormally high levels of both.
Humans ; Multiple Myeloma/complications* ; Fibroblast Growth Factor-23 ; Retrospective Studies ; Fibroblast Growth Factors/blood* ; Glucuronidase/blood* ; Male ; Female ; Middle Aged ; Renal Insufficiency/blood* ; Aged