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.

ObjectiveCerebrospinal fluid (CSF) plays a crucial role in maintaining the homeostasis of the central nervous system (CNS). CSF rapidly exchanges with interstitial fluid (ISF) via the glymphatic system within the brain parenchyma. CSF-ISF circulation and its associated mechanisms are often referred to as the brain lymphatic system. This system is connected directly to meningeal lymphatic vessels (mLVs), jointly performing the function of clearing metabolic waste from the CNS. Emerging evidence indicates that this system is closely associated with the onset and progression of neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD). Importantly, abnormal CSF circulation is not only a downstream consequence of AD pathology, but also a risk factor. In AD, the dynamics of CSF flow within the CNS are diminished, immune dysregulation occurs, and this may increase the risk of AD by exacerbating the burden of amyloid β-protein (Aβ). In the mouse model of AD, impaired CSF flow compromises this clearance function, leading to cognitive deficits. Clinically, acupuncture at cognition-related acupoints is commonly used for the prevention and treatment of AD. However, whether its therapeutic effects are mediated through the modulation of CSF dynamics remains unclear. This study aimed to evaluate the impact of acupuncture on CSF flow and investigate its acupoint specificity. MethodsMice were randomly assigned to experimental groups for the different electroacupuncture groups with the following acupoints: Baihui point (GV 20), Ear point, Neiguan point (PC 6), and Tianshu point (ST 25). Wild-type mice on a C57BL/6J background were used as controls. Fluorescent tracer was injected into the cisterna magna to label CSF flow. Fluorescence imaging was employed to assess the distribution of CSF within the brain before and after acupuncture stimulation. ResultsFollowing tracer injection into the cisterna magna, fluorescence signals rapidly reached the cerebellum and medulla—the regions closest to the injection site. Fluorescence intensity was higher in ventral brain regions compared to dorsal regions, likely due to greater vascular density in ventral areas facilitating CSF-ISF exchange. Electroacupuncture at the GV 20 produced the most pronounced enhancement of CSF across the whole brain, while stimulation at the ST 25 primarily augmented flow within subcortical regions. In contrast, electroacupuncture at the Ear point or the PC 6 had no observable effect on CSF in mice. ConclusionElectroacupuncture promotes CSF flow into the brain parenchyma in an acupoint-specific manner, with GV 20 exhibiting the most pronounced enhancement of CSF dynamics. These findings suggest that acupuncture-mediated facilitation of CSF flow may represent a potential therapeutic strategy for preventing or delaying age-related cognitive decline.

ObjectiveCerebrospinal fluid (CSF) plays a crucial role in maintaining the homeostasis of the central nervous system (CNS). CSF rapidly exchanges with interstitial fluid (ISF) via the glymphatic system within the brain parenchyma. CSF-ISF circulation and its associated mechanisms are often referred to as the brain lymphatic system. This system is connected directly to meningeal lymphatic vessels (mLVs), jointly performing the function of clearing metabolic waste from the CNS. Emerging evidence indicates that this system is closely associated with the onset and progression of neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD). Importantly, abnormal CSF circulation is not only a downstream consequence of AD pathology, but also a risk factor. In AD, the dynamics of CSF flow within the CNS are diminished, immune dysregulation occurs, and this may increase the risk of AD by exacerbating the burden of amyloid β-protein (Aβ). In the mouse model of AD, impaired CSF flow compromises this clearance function, leading to cognitive deficits. Clinically, acupuncture at cognition-related acupoints is commonly used for the prevention and treatment of AD. However, whether its therapeutic effects are mediated through the modulation of CSF dynamics remains unclear. This study aimed to evaluate the impact of acupuncture on CSF flow and investigate its acupoint specificity. MethodsMice were randomly assigned to experimental groups for the different electroacupuncture groups with the following acupoints: Baihui point (GV 20), Ear point, Neiguan point (PC 6), and Tianshu point (ST 25). Wild-type mice on a C57BL/6J background were used as controls. Fluorescent tracer was injected into the cisterna magna to label CSF flow. Fluorescence imaging was employed to assess the distribution of CSF within the brain before and after acupuncture stimulation. ResultsFollowing tracer injection into the cisterna magna, fluorescence signals rapidly reached the cerebellum and medulla—the regions closest to the injection site. Fluorescence intensity was higher in ventral brain regions compared to dorsal regions, likely due to greater vascular density in ventral areas facilitating CSF-ISF exchange. Electroacupuncture at the GV 20 produced the most pronounced enhancement of CSF across the whole brain, while stimulation at the ST 25 primarily augmented flow within subcortical regions. In contrast, electroacupuncture at the Ear point or the PC 6 had no observable effect on CSF in mice. ConclusionElectroacupuncture promotes CSF flow into the brain parenchyma in an acupoint-specific manner, with GV 20 exhibiting the most pronounced enhancement of CSF dynamics. These findings suggest that acupuncture-mediated facilitation of CSF flow may represent a potential therapeutic strategy for preventing or delaying age-related cognitive decline.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Objective:To analyze the efficacy of transjugular intrahepatic portosystemic shunt (TIPS) combined with main splenic artery embolization in the treatment of patients with portal hypertension upper gastrointestinal bleeding complicated with extensive portal vein thrombosis (PVT).Methods:This study was a prospective, single-center, open-label, single-arm clinical trial. In the first phase, 81 patients with portal hypertension upper gastrointestinal bleeding who were admitted to Beijing Shijitan Hospital, Capital Medical University from January 2018 to December 2018 were consecutively enrolled, including 57 males and 24 females, with the age of (51.3±10.4) years. During TIPS surgery, the pressure of the portal vein before and after the balloon blocking the splenic artery was measured to clarify the contribution of the splenic artery to portal hypertension. In the second stage, from January 2019 to December 2022, 104 patients with portal hypertension upper gastrointestinal bleeding complicated with extensive PVT were re-enrolled, including 71 males and 33 females, with the age of (50.9±12.5) years. TIPS combined with main splenic artery embolization was performed, and portal vein pressure was measured before and after embolization. Follow up on the postoperative esophageal and gastric varices of the patients in the second stage.Results:The portal vein pressures before and after the first stage of balloon occlusion of the splenic artery were (35.2±8.4) mmHg (1 mmHg=0.133 kPa) and (24.2±6.3) mmHg, respectively. The pressure after occlusion was lower than that before occlusion, and the difference was statistically significant ( t=10.54, P<0.001). The portal vein pressures before and after the second stage embolization were (36.1±9.5) mmHg and (21.1±4.7) mmHg respectively. The pressure after embolization was lower than that before embolization, and the difference was statistically significant ( t=13.47, P<0.001). In the second stage, among the 104 patients, the proportion of those whose varicose veins disappeared or improved 6 months after the operation was 43.3%(45/104) and 51.0%(53/104), respectively. There were no patients with aggravation or rebleeding due to rupture. One year later, 8 patients (7.7%) had aggravated or ruptured esophageal and gastric varices with bleeding. Two years later, 12 patients (11.5%) had aggravated or bleeding. Conclusion:TIPS combined with main splenic artery embolization can effectively reduce the portal vein pressure in patients with portal hypertension upper gastrointestinal bleeding complicated with extensive PVT, improve the degree of esophageal and gastric varices, and reduce the risk of gastrointestinal bleeding.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

The genome tagging project (GTP) plays a pivotal role in addressing a critical gap in the understanding of protein functions. Within this framework, we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411 (HA-tagged Ssp411) mouse model. This model is instrumental in probing the expression and function of Ssp411. Our research revealed that Ssp411 is expressed in the round spermatids, elongating spermatids, elongated spermatids, and epididymal spermatozoa. The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis. Nevertheless, rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions. Ssp411 is not detectable in metaphase II (MII) oocytes, zygotes, or 2-cell stage embryos, highlighting its intricate role in early embryonic development. These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP, fostering groundbreaking advancements in the fields of spermiogenesis and reproductive biology.
Animals ; Female ; Humans ; Male ; Mice ; Spermatids/metabolism* ; Spermatogenesis/physiology* ; Spermatozoa/metabolism* ; Thioredoxins/genetics*

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*