ObjectiveTo investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

ObjectiveTo investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

Brain-computer interface (BCI) is a neuro-engineering technology that establishes a direct communication pathway between the brain and external devices. It can realize bidirectional information interaction between the brain and external devices through real-time acquisition and decoding of brain signals, thereby completing brain state recognition and precise feedback regulation. This technology is promoting the transformation of the diagnosis and treatment model of neuropsychiatric diseases from “open-loop stimulation” to “closed-loop adaptation”. The brain regions and circuits involved in the neural mechanisms of addiction and sleep disorder are highly intertwined. Sleep-related brain rhythms provide a key time window for the intervention of addiction memory, and both have abnormal electrophysiological activities and functional imbalances in core neural circuits. This article reviews the latest research progress of closed-loop BCI in the fields of addiction and sleep disorder, explains the neural circuits and electrophysiological mechanisms of its regulation, and its limitations in diagnosis and treatment of the two diseases. In addition, it prospects individualized closed-loop intervention from the perspective of brain-body interaction, so as to provide reference for the clinical transformation of closed-loop BCI.

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.

Autosomal dominant polycystic kidney disease （ADPKD） is a systemic hereditary renal disorder and can affect multiple organs， and congenital hepatic fibrosis is one of the manifestations of liver involvement and is an important complication of ADPKD. Symptomatic management is currently the main treatment method for this disease， and disease-specific drugs such as tolvaptan have limited indications and cannot correct the underlying genetic defect. This article reports a case of ADPKD with congenital hepatic fibrosis， and sirolimus was identified as the individualized treatment regimen based on peripheral blood functional genomic analysis and drug sensitivity prediction platform. The patient achieved significant improvements in symptoms and quality of life after treatment， with a stable kidney volume. This case shows that functional genomics has a potential value in guiding individualized treatment of rare genetic disorders， which provides new treatment ideas and practice paths for similar patients.

OBJECTIVE: To establish foot and ankle models of different lateral collateral ligament injuries of ankle joint, and conduct finite element analysis on, and to explore the force conditions of subtalar articular cartilage during foot inversion movements under different gait stages and under different loads. METHODS: A normal ankle CT scan of a 30-year-old male healthy volunteer (heighted 175 cm and weighted 60 kg) was selected. The CT images were imported into software such as Mimics 21.0, Geomajic 2017, and Solidworks 2017 respectively, extract the normal ankle bone model. Then, the foot and ankle finite element models of different lateral collateral ligament injuries of ankle joint were constructed and divided into anterior talofibular ligament(ATFL) rupture group, ATFL and calcaneo fibular ligament (CFL) rupture group, ATFL, CFL and posterior talofibular ligament (PTFL) rupture group, and control group with intact ligament function by ANSYS 2021. Corresponding horizontal and vertical loads and torques were applied respectively on tibia and talus according to the force conditions of different phases to simulate landing phase, neutral and off-ground phase in walking gait. The changes in stress distribution area and stress peak of subtalar articular cartilage in the loading phase, neutral phase and off-ground phase gaits among four groups were observed. Simulate varus sprain action, apply different loads of 600, 1, 800, and 4, 200 N respectively, and changes in stress distribution area and the stress peak of subtalar articular cartilage among four groups of models were observed. RESULTS: In the gait simulation, the stress results of loading phase in ATFL fracture group, ATFL and CFL fracture groups, ATFL, CFL and PTFL fracture groups, and control group were 0.889 54, 0.960 89, 1.139 20, and 0.722 64 MPa, respectively. The neutral response force results were 1.250 60, 1.358 50, 1.363 70, 1.246 40 MPa respectively;the results of corresponding forces off-ground phase were 1.029 90, 1.138 70, 1.145 90 and 0.832 40 MPa respectively. In the inversion simulation, the stresses of ATFL fracture group, ATFL and CFL fracture groups, ATFL, CFL and PTFL fracture groups, and control group under load of 600 N were 2.191 3, 2.208 5, 2.215 7, and 2.156 6 MPa respectively. The stresses under a load of 1 800 N were 7.134 7, 9.715 2, 10.064 0, and 7.107 0 MPa respectively;the stresses under a load of 4 200 N were 17.435 0, 25.309 0, 26.119 0 and 16.010 0 MPa respectively. CONCLUSION The lateral collateral ligament of ankle joint plays an important role in the stability of the subtalar joint, especially CFL plays an important role in restricting calcaneal varus. If these ligaments are damaged, it will cause instability of the subtalar joint and further lead to lesions in the subtalar articular cartilage. Relevant exercises should be reduced or the ligament injuries should be treated in a timely manner.
Humans ; Finite Element Analysis ; Male ; Adult ; Cartilage, Articular/physiopathology* ; Ankle Injuries/physiopathology* ; Ankle Joint/physiopathology* ; Biomechanical Phenomena ; Subtalar Joint/injuries* ; Tomography, X-Ray Computed

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*