ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

AIM: To evaluate the safety and efficacy of low-dose transscleral cyclophotocoagulation(TSCP)in the management of persistent ocular hypertension after an acute attack of angle-closure glaucoma(AACG).METHODS:This retrospective study enrolled patients diagnosed with persistent ocular hypertension after an acute AACG attack at the No.988 Hospital of the Joint Logistics Support Force of the Chinese PLA between September 2023 and September 2024. All patients underwent low-dose TSCP using a semiconductor diode laser. Subsequent cataract surgery combined with goniosynechialysis was performed once intraocular pressure(IOP)was stabilized. Changes in anterior chamber depth(ACD), best-corrected visual acuity(VA), and IOP were compared before and after TSCP, as well as before and after phacoemulsification. Post-TSCP complications were also documented.RESULTS: A total of 21 patients(21 eyes)were enrolled, including 8 males and 13 females, with a mean age of 67.95±7.25 y. Compared with pre-cyclophotocoagulation values, ACD increased significantly at 3 d post-TSCP(1.49±0.18 vs 1.22±0.21 mm; P<0.001). BCVA and IOP decreased significantly at 1 d post-TSCP, pre-phacoemulsification, 1 wk post-phacoemulsification, and 1 mo post-phacoemulsification compared with pre-TSCP IOP(all P<0.01). Regarding postoperative complications, 2 eyes experienced pain on the day of the procedure, 5 eyes developed mild corneal endothelial folds, 2 eyes exhibited moderate anterior chamber inflammatory reaction, and 12 eyes showed shallow ciliary body detachment. No serious complications occurred during the 1-month follow-up period.CONCLUSION:Low-dose TSCP appears to be an effective bridging therapy for patients with persistent ocular hypertension following an AACG attack. It facilitates rapid IOP reduction, alleviates symptoms, and helps preserve visual function with a favorable safety profile, thereby reducing the risks associated with subsequent intraocular surgery.

ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

The oocyte， as the origin of life， provides half the chromosomes to the embryo and supplies the proteins， substrates， energy， and other support necessary for embryonic development. It is the decisive factor determining the embryo's developmental potential. Infertility caused by reproductive endocrine diseases targets the oocyte as the final target cell. Improving oocyte quality represents a key and difficult point in the field of modern reproductive medicine. The decline of oocyte quality is related to meiosis abnormalities， DNA damage， mitochondrial dysfunction， oxidative stress， and other mechanisms. For oocyte quality problems， there is no unified international guideline to recommend drugs. Because the drug intervention research on oocytes involves strict clinical ethical restrictions， the current relevant research only stays in the animal and in vitro experimental stage and has not yet been applied to the clinic. Traditional Chinese medicine compound formula has a multi-target and multi-pathway regulation mechanism and is widely used in clinics. More and more research began to pay attention to the potential mechanism of traditional Chinese medicine compound formulas in improving oocyte quality. Traditional Chinese medicine compound formula has the advantages of multi-target and multi-channel synergy as well as better safety， individualization， and conformity to clinical ethics in improving oocyte quality. This article systematically reviewed the research progress on traditional Chinese medicine compound formula interventions for oocyte quality， aiming to summarize existing findings and provide recommendations to improve oocyte quality and optimize the clinical diagnosis and treatment of female infertility within traditional Chinese medicine.

The oocyte， as the origin of life， provides half the chromosomes to the embryo and supplies the proteins， substrates， energy， and other support necessary for embryonic development. It is the decisive factor determining the embryo's developmental potential. Infertility caused by reproductive endocrine diseases targets the oocyte as the final target cell. Improving oocyte quality represents a key and difficult point in the field of modern reproductive medicine. The decline of oocyte quality is related to meiosis abnormalities， DNA damage， mitochondrial dysfunction， oxidative stress， and other mechanisms. For oocyte quality problems， there is no unified international guideline to recommend drugs. Because the drug intervention research on oocytes involves strict clinical ethical restrictions， the current relevant research only stays in the animal and in vitro experimental stage and has not yet been applied to the clinic. Traditional Chinese medicine compound formula has a multi-target and multi-pathway regulation mechanism and is widely used in clinics. More and more research began to pay attention to the potential mechanism of traditional Chinese medicine compound formulas in improving oocyte quality. Traditional Chinese medicine compound formula has the advantages of multi-target and multi-channel synergy as well as better safety， individualization， and conformity to clinical ethics in improving oocyte quality. This article systematically reviewed the research progress on traditional Chinese medicine compound formula interventions for oocyte quality， aiming to summarize existing findings and provide recommendations to improve oocyte quality and optimize the clinical diagnosis and treatment of female infertility within traditional Chinese medicine.

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.

Objective To analyze the genomic characteristics of Legionella pneumophila (L. pneumophila) isolated from industrial circulating cooling water in workplace. Methods A total of 20 L. pneumophila strains isolated from industrial circulating cooling water collected from eight chemical enterprises were selected as the research subjects. Whole-genome sequencing was performed on the strains, followed by multilocus sequence typing (MLST), whole-genome single nucleotide polymorphism analysis, virulence factor profiling, and antibiotic resistance gene detection. Results The dominant MLST typing among the 20 L. pneumophila strains was ST2. Serogroup 1 (Lp1) strains exhibited high genetic diversity. Strains from different enterprises showed substantial genomic diversity, suggesting possible inter-enterprise dissemination. Each isolate harbored 175-295 virulence genes; among them, virulence genes were identified, and 139 genes were detected in all the 20 strains. These genes primarily included those related to the Dot/Icm type Ⅳ bacterial secretion system, flagellar synthesis and motility, and type Ⅳ pili. The number of virulence genes carried by L. pneumophila strains of different ST types differed (P<0.01), with unidentified sequence types harboring more virulence genes than other STs (P<0.01). A total of four resistance genes were predicted, including aminoglycoside phosphotransferase-encoding gene APH(9)-Ia, carbapenemase-encoding gene OXA-29, and efflux pump genes-encoding genes LpeA and LpeB, with detection rates of 100.00%, 100.00%, 10.00%, and 10.00%, respectively. These genes may confer resistance to cephalosporins, penicillins, and aminoglycosides, and all strains were multidrug resistance. Conclusion L. pneumophila isolated from industrial recirculating cooling water exhibits high genetic diversity, strong pathogenicity, and significant multidrug resistance potential.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Five saponins were isolated from the kernels of Momordica cochinchinensis, by macroporous resin, silica gel, ODS column chromatography, and semi preparative HPLC. Based on MS and NMR analysis, combining with alkaline hydrolysis and acid hydrolysis, their structures were identified as: gypsogenin-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (1), quillaic acid-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (2), gypsogenin-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (3), quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (4), 18α-quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside (5). Compounds 1-5 were new compounds, and named as mubezhisides A, B, C, D, E, respectively. They all could obviously inhibited the growth of Candida albicans, C. parapsilosis, and C. tropicalis.

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*