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.

Non-invasive body fluids contain a wealth of health-related biomarkers.Monitoring these biomarkers can provide valuable information for disease diagnosis,health management,drug abuse screening,and sports performance optimization.In this work,a carbon nanotube-polysiloxane(CNT-Putty)-based wearable electrochemical sensor was constructed on glove by screen-printing method.This electrode material had not only a simple composition,but also a relatively simple synthesis process.In addition,the electrode exhibited superior electrochemical performance compared to commercial screen-printed electrodes.When applied to uric acid(UA)detection in three different body fluids,the CNT-Putty working electrode demonstrated excellent linearity,selectivity,and a low detection limit.The wearable glove sensor could successfully monitor UA levels in body fluids under varying dietary conditions,indicating its potential for personalized UA monitoring and management.

An efficient analytical method was developed for simultaneous detection of alkylamines and alkylamides in food packaging plastics using liquid chromatography-high resolution mass spectrometry(LC-HRMS).Based on the physicochemical properties of alkylamines and alkylamides,as well as the complexity of plastic samples,sample pretreatment and chromatographic-mass spectrometric parameters were optimized.The samples were extracted by vortex-ultrasonic extraction with a methanol-acetonitrile mixture for 15 min,followed by nitrogen evaporation to concentrate the extract,reconstitution,and analysis.The chromatographic mobile phase consisted of 0.1%formic acid aqueous solution and acetonitrile,and a gradient elution was used.The electrospray ionization(ESI)source was operated in positive ion mode,and mass spectrometry data were collected in full scan and data-dependent acquisition modes.Quantification was performed using an isotope-labeled internal standard method.The results showed that within the quantification range of 1-1000 ng/mL,the calibration curves exhibited good linearity(R2>0.99).Some compounds interfered with the validation experiments at higher concentrations,so only 10 kinds of target analytes were validated.Using a mixed food packaging plastic matrix,the recoveries at spiking levels of 40,400,and 4000 ng/g were mostly between 66.0%and 117.1%,with relative standard deviations ranging from 0.6%to 10.6%.The method was applied to detect 14 food packaging plastic samples,and the results showed that the concentrations of alkylamines and alkylamides ranged from not detected to 8924 ng/g.This method offered high sensitivity and accuracy,and was suitable for the screening and quantitative determination of alkylamines and alkylamides in plastics.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

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*

This study using maltodextrin as raw material, 1%-5% polyvinylpyrrolidone K30 as template agent, 1%-5% ammonium bicarbonate as pore-forming agent, curcumin and ibuprofen as model drugs. Porous maltodextrin was prepared by template and pore-forming agent methods, respectively. The structure and drug delivery behavior of porous maltodextrin prepared by different technologies were comprehensively characterized. The results showed that the porous maltodextrin prepared by pore-forming agent method had larger specific surface area (6.449 4 m²·g^-1) and pore size (32.804 2 nm), which was significantly better than that by template agent method (3.670 2 m²·g^-1, 15.278 5 nm). The adsorption kinetics between porous maltodextrin prepared by pore-forming agent method and curcumin were suitable for quasi-first order adsorption kinetic model, and that between porous maltodextrin and ibuprofen were suitable for quasi-second order adsorption kinetic model. While the adsorption kinetics between porous maltodextrin prepared by template agent method and two model drugs were both suitable for the quasi-first order adsorption kinetic model. In addition, the dissolution behavior analysis showed that the porous maltodextrin prepared by the two technologies can significantly improve the dissolution behavior of insoluble drugs, and the drug release was both carried out by diffusion mechanism, which suitable for the Peppas kinetic release model, but the porous maltodextrin prepared by template agent method had a faster release rate. The change of nozzle diameter had no significant effect on the adsorption process and drug release behavior of porous maltodextrin. In conclusion, the porous maltodextrins prepared by two different technologies were both beneficial to the delivery of insoluble drugs, and the template agent method was the best for delivery of insoluble drugs. This study can provide theoretical basis for the preparation of porous particles, promote the application of porous particles in insoluble drugs, and improve the bioavailability of insoluble drugs.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

The steps for installation and withdrawal of WYD2000 field surgical lamp were introduced.The failures and causes of broken cross-arm connector of WYD2000 field surgical lamp were analyzed.The problems of WYD2000 field surgical lamp in vulnerability to breaking and difficulty in maintenance were solved by designing and manufacturing a special maintenance tool and optimizing the materials and fixing mode of cross-arm connection.References were provided for main-tenance and improvement of WYD2000 field surgical lamp.[Chinese Medical Equipment Journal,2024,45(4):116-118]

Objective: To compare the safety and efficacy of transmesenteric vein extrahepatic portosystemic shunt (TEPS) and transjugular intrahepatic portosystemic shunt (TIPS) in the treatment of cavernous transformation of the portal vein (CTPV). Methods: The clinical data of CTPV patients with patency or partial patency of the superior mesenteric vein treated with TIPS or TEPS treatment in the Department of Vascular Surgery of Henan Provincial People's Hospital from January 2019 to December 2021 were selected. The differences in baseline data, surgical success rate, complication rate, incidence rate of hepatic encephalopathy, and other related indicators between TIPS and TEPS group were statistically analyzed by independent sample t-test, Mann-Whitney U test, and Chi-square test. Kaplan-Meier survival curve was used to calculate the cumulative patency rate of the shunt and the recurrence rate of postoperative portal hypertension symptoms in both groups. Results: The surgical success rate (100% vs. 65.52%), surgical complication rate (6.67% vs. 36.84%), cumulative shunt patency rate (100% vs. 70.70%), and cumulative symptom recurrence rate (0% vs. 25.71%) of the TEPS group and TIPS group were statistically significantly different (P < 0.05). The time of establishing the shunt [28 (2141) min vs. 82 (51206) min], the number of stents used [1 (12) vs. 2 (15)], and the length of the shunt [10 (912) cm vs. 16 (1220) cm] were statistically significant between the two groups (t = -3.764, -4.059, -1.765, P < 0.05). The incidence of postoperative hepatic encephalopathy in the TEPS group and TIPS group was 6.67% and 15.79% respectively, with no statistically significant difference (Fisher's exact probability method, P = 0.613). The pressure of superior mesenteric vein decreased from (29.33 ± 1.99) mmHg to (14.60 ± 2.80) mmHg in the TEPS group and from (29.68 ± 2.31) mmHg to (15.79 ± 3.01) mmHg in TIPS group after surgery, and the difference was statistically significant (t = 16.625, 15.959, P < 0.01). Conclusion: The best indication of TEPS is in CTPV patients with patency or partial patency of the superior mesenteric vein. TEPS improves the accuracy and success rate of surgery and reduces the incidence of complications.
Humans ; Portal Vein/surgery* ; Portasystemic Shunt, Transjugular Intrahepatic/methods* ; Hepatic Encephalopathy/etiology* ; Treatment Outcome ; Hypertension, Portal/complications* ; Retrospective Studies ; Gastrointestinal Hemorrhage/etiology*