OBJECTIVE To investigate the potential mechanism by which Juanxiao decoction improves bronchial asthma （hereinafter referred to as “asthma”） based on the nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3） inflammasome signaling pathway. METHODS Female SD rats were randomly assigned to normal group， model group and Juanxiao decoction low-， medium- and high-dose groups （0.36， 0.72 and 1.44 g/kg， calculated based on crude drug weight）， as well as positive control group （Dexamethasone acetate tablets， 0.2 mg/kg）， with 10 rats in each group. Except for the normal group， asthma models were established in the remaining groups via intraperitoneal injection of ovalbumin combined with aluminum hydroxide， followed by nebulized inhalation of ovalbumin. On day 14 of the experiment， rats in each group received intragastric administration of the corresponding solution or normal saline， once a day， for 7 consecutive days. Following the final administration， the following parameters were measured in each group： lung function indexes （forced vital capacity， forced expiratory volume in 0.3 second， peak expiratory flow）， serum levels of inflammatory markers （interleukin-1β， interleukin- 18）， and the percentages of inflammatory cells （lymphocytes， eosinophils， neutrophils） in bronchoalveolar lavage fluid. Histopathological changes in lung tissue were observed， and the protein and mRNA expressions of nuclear factor-kappa B （NF- κB）， NLRP3 and caspase-1 in lung tissue were detected. RESULTS Compared with the normal group， pathological changes such as alveolar wall thickening and inflammatory cell infiltration were observed in rats in the model group. All pulmonary function indicators were significantly reduced in rats in the model group and the administration groups. The levels of inflammatory markers， the percentages of inflammatory cells， and the protein and mRNA expressions of NF-κB， NLRP3 and caspase-1 were significantly elevated or up-regulated （P＜0.05）. Compared with the model group， pathological changes in rats in each dosage group of Juanxiao decoction were significantly alleviated， and all quantitative indicators showed dose-dependent improvements （P＜0.05）. CONCLUSIONS Juanxiao decoction can reduce airway inflammatory responses in asthmatic rats， alleviate lung function impairment， and improve pathological changes such as inflammatory cell infiltration. Those effects may be related to the inhibition of the NLRP3 inflammasome signaling pathway.

Objective To explore the wearing status and actual noise reduction effect of hearing protectors among noise workers in a typical automobile manufacturing enterprise. Methods In April 2024, an occupational hazard factor testing was carried out in an automobile manufacturing industry, and at the same time, the hearing protection fit test was conducted for noise workers. Intervention and guidance were provided to those who did not pass the minimum standard of baseline PAR. The difference in PAR between baseline and post-intervention was compared, and the effectiveness of hearing protector wearing method training was evaluated. Results The exceeding rate of the company's noise operation post was 50.77% (66/130). The baseline PAR of the subjects with working experience of less than 15 years and wearing hearing protectors throughout noisy work was higher, and the differences were statistically significant (P<0.05). Compared with those with 80dB≤L_{EX, 8h}<85dB, more research subjects with L_{EX, 8h}≥85dB failed baseline PAR (39.13%). After intervention, the PAR of the subjects who did not pass the minimum standard of baseline PRA increased from 2.0 (0.0, 5.3) to 17.0 (14.8, 20.0), and the protection level was significantly improved, and the difference was statistically significant (P<0.01). Conclusion The individual fit test of hearing protector is an important means to evaluate the actual noise reduction level of hearing protector and guide the selection of hearing protection models. Corporate training can help improve the PAR of hearing protectors.

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.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

AIM: To investigate the abnormal conditions and change patterns of accommodative facility in patients with different refractive states before and after small incision lenticule extraction(SMILE)surgery.METHODS:A prospective clinical cohort study was conducted. A total of 59 patients(118 eyes)who underwent SMILE surgery and had visual function files established in our hospital from June to December 2023 were randomly selected, including 37 males and 22 females, aged 18-35 years(with an average age of 25.19±5.65 years). According to the preoperative spherical equivalent(SE), they were divided into two groups: the low-to-moderate myopia group(SE≥-6.00 DS)with 40 patients(80 eyes), and the high myopia group(SE<-6.00 DS)with 19 patients(38 eyes). The monocular and binocular accommodative facility before surgery and at 1 wk and 1 mo after surgery were compared, and the changes in accommodative facility before and after SMILE surgery in the two groups of patients were analyzed.RESULTS:All surgeries were completed successfully. In the low-to-moderate myopia group, 33 cases(66 eyes)completed the 1-month follow-up after surgery, with a loss to follow-up rate of 17.5%(7/40). In the high myopia group, 15 patients(30 eyes)completed the 1-month follow-up after surgery, with a loss to follow-up rate of 21.1%(4/19). After SMILE surgery, the uncorrected visual acuity and SE of both low-to-moderate myopia and high myopia were significantly improved(all P<0.05). The accommodative facility of the right eyes in all the patients at 1 mo after surgery was better than that before surgery and at 1 wk after surgery(P=0.002, 0.006), the accommodative facility of the left eyes was significantly increased at 1 mo after surgery than that at 1 wk after surgery(P=0.005), and the binocular accommodative facility at 1 mo after surgery was significantly increased compared with that before surgery(P<0.017). Furthermore, there were statistical significance in accommodative facility of the right eyes in the low-to-moderate group at 1 mo compared with that before surgery and at 1 wk after surgery(P=0.011, 0.004); it was significantly increased in the left eyes at 1 mo after surgery compared with that at 1 wk after surgery(P=0.001), and binocular accommodative facility at 1 mo after surgery was significantly better than that before surgery(P<0.001). Furthermore, there was no statistical significance in the right, left and binocular accommodative facility of patients in the high myopia group(all P>0.017).CONCLUSION: After SMILE surgery, the monocular accommodative facility shows a transient decrease and then exceeds the preoperative level at 1 mo after surgery, and the binocular accommodative facility gradually improves after surgery. SMILE surgery has a positive impact on the monocular and binocular accommodative facility in patients with low-to-moderate myopia, but has no significant impact on the accommodative facility in patients with high myopia. It is of clinical significance to strengthen the detection of monocular and binocular accommodative facility before and after SMILE surgery.

Alzheimer's disease(AD)is a neurodegenerative disease with highly heterogeneous pathological and clinical manifesta-tions,and it is the most common cause of dementia.This heterogeneity poses challenges for diagnosis,treatment,and evaluating novel pharmacological efficacy.This review summarizes the latest progress in the major clinical subtypes of AD based on clinical manifesta-tions,genetic,and pathological features.Early-onset and late-onset AD clinical subtypes may share the same symptoms but differ in etiology,age of onset,mode of presentation,disease progression,and associated comorbidities.Typical and atypical AD differ signifi-cantly in clinical manifestations,pathological features,and diagnostic criteria.Research on AD subtypes based on imaging and omics data has also made considerable progress.This review also outlines the molecular pathological heterogeneity of AD.A deep understand-ing of these heterogeneities is crucial for diagnosis,the formulation of pharmacological treatment strategies,and clinical management.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the preliminary results of using the UreteroPyeloVisClear Catheter (VCC) in the treatment of ureteral stones.Methods:A retrospective analysis was conducted on the clinical data of 18 patients with ureteral stones who underwent treatment with VCC at Beijing Tsinghua Changgung Hospital from November 2023 to March 2024. The cohort consisted of 15 men and 3 women, with a mean age of 53 years (range: 27-75 years). The preoperative CT measurements showed that the mean maximum stone diameter was 9 mm (range: 3-18 mm), and the mean maximum CT value of the stones was 870 HU (range: 260-1 480 HU). The distribution of stones was as follows: 3 cases in the upper ureter, 8 in the middle ureter, and 7 in the lower ureter. Gravity-assisted perfusion was used, and all patients underwent VCC combined with Holmium laser lithotripsy, with flexible ureteroscopy used if necessary. A ureteral stent was routinely placed for 2 weeks postoperatively. Perioperative conditions and complications were analyzed.Results:All 18 patients successfully underwent VCC lithotripsy, with one patient experiencing stone migration during the procedure. The average operation time was 53 minutes (range: 20-100 minutes), and the average lithotripsy time was 25.5 minutes (range: 6–60 minutes). There were no significant changes in serum creatinine or hemoglobin levels on the first postoperative day. The average hospital stay was 2 days (range: 1–3 days). One patient experienced a fever (maximum temperature of 38.5℃), which resolved with antibiotic treatment. The visual analogue scale (VAS) scores on postoperative day 1 were 0 for 15 patients, 2 for 1 patient, 3 for 1 patient, and 4 for 1 patient. No complications of Clavien-Dindo grade Ⅱ or higher were observed. At 1-month follow-up, the stone-free rate (SFR) was 100%(18/18), and no hydronephrosis was observed in the affected kidney.Conclusions:The results of this study indicates that VCC is a safe and effective method for treating ureteral stones, with a low incidence of postoperative complications and a high stone clearance rate.

Objective:To investigate the efficacy of fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), aspartate aminotransferase to platelet count ratio (APRI), liver stiffness value (LSM), and Agile 3+ score and their combined model in predicting advanced-stage liver fibrosis in patients with chronic hepatitis B (CHB) combined with metabolic-associated fatty liver disease (MAFLD).Methods:A multicenter retrospective cohort study was conducted on the BMOVE population.Nine hundred twenty CHB cases combined with MAFLD who underwent liver biopsy at seven medical centers in China from April 2006 to December 2023 were included. The patients were divided into advanced-stage liver fibrosis (159 cases) and non-advanced-stage liver fibrosis (761 cases) according to the Scheuer's scoring system.The area under the receiver operating characteristic curve (AUROC), decision curve, and calibration curve analysis were used to evaluate the efficacy of the firbrosis-4 index (FIB-4) score, NFS score, APRI index, LSM, and Agile 3+ score and their combined model in predicting advanced-stage fibrosis. The liver fibrosis grade of all patients was diagnosed by liver biopsy. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each scoring model and combined model, as well as the proportion of correctly classified patients, were calculated based on different cutoff values.Results:AUROC analysis showed that Agile 3+ (0.814, 95% CI: 0.787-0.838) and LSM (0.805, 95% CI: 0.778-0.829) had similar accuracy and were superior to FIB-4 (0.721, 95% CI: 0.691-0.749), NFS (0.687, 95% CI: 0.656-0.716) and APRI ( 0.689, 95% CI: 0.658-0.718); however, HBV DNA level and HBV e antigen status had no effect on this outcome. Decision curve analysis showed that interventions based on LSM and Agile 3+ had provided higher net benefits compared with serological scores. Calibration curves showed that Agile 3+ had better predicitive accuracy than all other models. Agile 3+ had the highest PPV (0.54), minimal uncertainty interval (11.6%), and the highest proportion of correctly classified patients (76%); followed by LSM (PPV: 0.43, uncertainty interval: 15.5%, correct classification rate: 66%), and FIB-4 (PPV: 0.42, uncertainty interval: 26.1%, correct classification rate: 62.6%) in terms of identifying advanced-stage liver fibrosis. Combined model analysis demonstrated that FIB-4 combined with Agile 3+ had improved the correct classification rate and reduced the proportion of missed patients compared with FIB-4 combined with LSM. Conclusion:The Agile 3+ score is superior than LSM, FIB-4, NFS, and APRI index at identifying advanced-stage fibrosis in patients with CHB combined with MAFLD. This study supports the use of FIB-4 index combined with Agile 3+ for risk stratification in patients with CHB combined with MAFLD.