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.

ObjectiveNeuroinflammation plays a crucial role in both the onset and progression of ischemic stroke, exerting a significant impact on the recovery of the central nervous system. Excessive neuroinflammation can lead to secondary neuronal damage, further exacerbating brain injury and impairing functional recovery. As a result, effectively modulating and reducing neuroinflammation in the brain has become a key therapeutic strategy for improving outcomes in ischemic stroke patients. Among various approaches, targeting immune regulation to control inflammation has gained increasing attention. This study aims to investigate the role of in vitro induced regulatory T cells (Treg cells) in suppressing neuroinflammation after ischemic stroke, as well as their potential therapeutic effects. By exploring the mechanisms through which Tregs exert their immunomodulatory functions, this research is expected to provide new insights into stroke treatment strategies. MethodsNaive CD4⁺ T cells were isolated from mouse spleens using a negative selection method to ensure high purity, and then they were induced in vitro to differentiate into Treg cells by adding specific cytokines. The anti-inflammatory effects and therapeutic potential of Treg cells transplantation in a mouse model of ischemic stroke was evaluated. In the middle cerebral artery occlusion (MCAO) model, after Treg cells transplantation, their ability to successfully migrate to the infarcted brain region and their impact on neuroinflammation levels were examined. To further investigate the role of Treg cells in stroke recovery, the changes in cytokine expression and their effects on immune cell interactions was analyzed. Additionally, infarct size and behavioral scores were measured to assess the neuroprotective effects of Treg cells. By integrating multiple indicators, the comprehensive evaluation of potential benefits of Treg cells in the treatment of ischemic stroke was performed. ResultsTreg cells significantly regulated the expression levels of both pro-inflammatory and anti-inflammatory cytokines in vitro and in vivo, effectively balancing the immune response and suppressing excessive inflammation. Additionally, Treg cells inhibited the activation and activity of inflammatory cells, thereby reducing neuroinflammation. In the MCAO mouse model, Treg cells were observed to accumulate in the infarcted brain region, where they significantly reduced the infarct size, demonstrating their neuroprotective effects. Furthermore, Treg cell therapy notably improved behavioral scores, suggesting its role in promoting functional recovery, and increased the survival rate of ischemic stroke mice, highlighting its potential as a promising therapeutic strategy for stroke treatment. ConclusionIn vitro induced Treg cells can effectively suppress neuroinflammation caused by ischemic stroke, demonstrating promising clinical application potential. By regulating the balance between pro-inflammatory and anti-inflammatory cytokines, Treg cells can inhibit immune responses in the nervous system, thereby reducing neuronal damage. Additionally, they can modulate the immune microenvironment, suppress the activation of inflammatory cells, and promote tissue repair. The therapeutic effects of Treg cells also include enhancing post-stroke recovery, improving behavioral outcomes, and increasing the survival rate of ischemic stroke mice. With their ability to suppress neuroinflammation, Treg cell therapy provides a novel and effective strategy for the treatment of ischemic stroke, offering broad application prospects in clinical immunotherapy and regenerative medicine.

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Forsythia suspensa is a traditional Chinese medicine and a commonly used landscaping plant. Its dried fruit is used in medicine for its functions of clearing heat, removing toxins, reducing swelling, dissipating masses, and dispersing wind and heat. It possesses extremely high medicinal and economic value. However, the genetic differentiation and diversity of its wild populations remain unclear. In this study, chloroplast genome sequences were obtained from 15 wild individuals of F. suspensa using high-throughput sequencing technology. The sequence characteristics and intraspecific variations were analyzed. The results were as follows:(1) The full length of the F. suspensa chloroplast genome ranged from 156 184 to 156 479 bp, comprising a large single-copy region, a small single-copy region, and two inverted repeat regions. The chloroplast genome encoded a total of 132 genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes.(2) A total of 166-174 SSR loci, 792 SNV loci, and 63 InDel loci were identified in the F. suspensa chloroplast genome, indicating considerable genetic variation among individuals.(3) Population structure analysis revealed that F. suspensa could be divided into five or six groups. Both the population structure analysis and phylogenetic reconstruction results indicated significant genetic variation within the wild populations of F. suspensa, with no obvious correlation between intraspecific genetic differentiation and geographical distribution. This study provides new insights into the genetic diversity and differentiation within F. suspensa species and offers additional references for the conservation of species diversity and the utilization of germplasm resources in wild F. suspensa.
Genome, Chloroplast ; Forsythia/classification* ; Phylogeny ; Genetic Variation ; Chloroplasts/genetics* ; Microsatellite Repeats

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

Haloacetic acids(HAAs),as a class of disinfection byproducts in drinking water,pose potential threats to human health,so the rapid,accurate and simultaneous detection of HAAs is of great significance for ensuring drinking water safety.Aiming at the challenges in HAAs detection and risk analysis,a novel method for synchronous rapid detection of seven kinds of HAAs in drinking water based on in situ derivatization technology and headspace gas chromatography was developed in this study.Through single-factor optimization experiments,the optimal reaction parameters for in situ derivatization were determined,including the type and dosage of salting-out agent,the acidity of reaction system,the amount of phase transfer catalyst,the dosage of derivatization agent,and the extraction solvent volume.Methodologic validation showed that the seven kinds of HAAs exhibited excellent linear relationships within their respective detection concentration ranges(R2>0.998).The method detection limits(MDLs)ranged from 0.04 to 0.33 μg/L,and the limits of quantification(LOQs)were between 0.14 and 1.34 μg/L.For real water samples,the average spiked recoveries of the seven HAAs ranged from 90.9%to 107.7%,with relative standard deviation(RSDs)between 1.55%and 6.49%,and the HAAs contents in all tested samples were below the limits specified in the Standards for Drinking Water Quality(GB 5749-2022)of China.This method was featured with simple operation,fast analysis speed,high sensitivity,and good accuracy,providing an efficient and reliable technical support for routine monitoring of HAAs contaminants in drinking water and showing promising application value for widespread promotion.

Objective:The components of Rubus parvifolius L. were analyzed based on UPLC-MS/MS technology and combined with network pharmacology analysis to explore the mechanism of action of Rubi Parvifolii Radix in treating inflammation, cough, fever, influenza and sore throat. Method:The chemical constituents of Rubi Parvifolii Radix were identified according to the information of mass spectrometry. The network pharmacology was used to analyze the corresponding targets and related pathways of its chemical components, and the "component-target-pathway" interaction diagram was drawn. PyMOL 2.5.7 software wasused to perform molecular docking between active components and key targets.Results:Twenty chemical components were identified by UPLC-MS/MS, and 15 components were screened out by network pharmacology, which can be used as quality markers of Rubi Parvifolii Radix, namely Azelaic acid, Procyanidol B3, Caprolactam, Bis (2-ethylhexyl) adipate, Cryptochlorogenic acid, 3-O-Feruloylquinic, Ellagic acid, Aurantiamide acetate, 2 α,3 β,19 α,23-Tetrahydroxyurs-12-en-28-oic acid, L-Epicatechin, (E)-3-Indoleacrylic acid, Euscaphic acid, Suberic acid, Diisononyl phthalate and Prodelphinidin T4. Molecular docking showed that 5 compounds compared with the reference substance could bind to the target proteins of disease well. Conclusions:The 15 active ingredients in Rubi Parvifolii Radix, including Caprolactam and (E)-3-Indoleacrylic acid, may play a therapeutic role in treating colds, high fever, sore throat, and inflammation by acting on targets such as AKT1 and TNF. This provides a certain reference for the clinical application of Rubi Parvifolii Radix.

Objective:To analyze the extraction, chemical composition, antioxidant, and anti-inflammatory activity of the TCM formula essential oil for the treatment of upper respiratory tract infections (URTI); To provide a scientific basis for its further development.Methods:The formula essential oil was extracted using the steam distillation method and analyzed for chemical composition by gas chromatography-mass spectrometry (GC-MS). The DPPH, ABTS scavenging ability, and hydroxyl radical scavenging ability of volatile oils were measured. The effect of the essential oil on the viability of RAW264.7 cells was assessed using the CCK-8 assay. ELISA and Western blot methods were used to determine the effects of volatile oil on LPS induced inflammatory cytokines IL-6 and TNF-α.Results:The average extraction rate of the formula essential oil was 1.12%, with a density of 0.973 2 g/ml. Twelve main chemical components were identified, with 1,8-cineole (42.9%) and patchoulol (19.9%) being the predominant constituents. The essential oil exhibited DPPH and ABTS radical scavenging capacities of 52% and 59%, respectively, and a hydroxyl radical scavenging capacity exceeding 70%. Essential oil could reduce the levels of IL-6 and TNF-α ( P<0.05). Conclusion:TCM formula essential oil for the treatment of URTI contains multiple bioactive components and demonstrates significant antioxidant and anti-inflammatory effects.

Objective To specifically extract and analyze nascent proteins synthesized by bone marrow mesenchymal stem cells(BMSCs)after transplantation into ischemic hearts using a technique employing mutant methionyl-tRNA synthetase(MetRSL247G)for nascent protein labeling,in order to explore the potential mechanisms of action in BMSCs post-transplantation.Methods Point mutation at position 274 of the MetRS gene in BMSCs was induced via lentiviral infection to enable azidonorleucine(ANL)-mediated labeling of nascent proteins in BMSCs.The labeling efficiency was verified by means of fluorescent non-canonical amino-acid tagging(FUNCAT).Thirty healthy female C57BL/6J mice(8-10 weeks old)were divided into control and experimental groups,with 15 mice in each group.The acute myocardial infarction model was constructed by ligating the left anterior descending coronary artery in experimental group,while control mice underwent only thoracotomy without coronary ligation.After modeling,both groups received intramyocardial injections of MetRSL247G-modified BMSCs(MetRSL247G-BMSCs)at 3 different sites in the peri-infarct ischemic region.Mice were intraperitoneally injected with ANL every 6 hours for 4 times on postoperative days 0,2,and 6(n=5 for each time point)respectively,euthanized 24 h after the last injection,and cardiac tissues were isolated.The newly synthesized and labeled proteins produced by BMSCs after transplantation into the myocardium of experimental and control groups were collected,using an enrichment technique for ANL-tagged proteins and liquid chromatography-tandem mass spectrometry(LC-MS)analysis.Gene ontology(GO)analysis,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis,protein-protein interaction(PPI)analysis,and heatmap visualization analysis were performed to identify differentially expressed proteins at the 3 time points and screen key pathways and genes.Results Under fluorescence microscopy,the MetRSL247G lentivirus-infected BMSCs were observed to be labelled with mCherry signals,confirming the successful construction of the MetRSL247G-BMSCs cell line.Green fluorescent signals were detected only in nascent proteins in culture medium containing both MetRSL247G-BMSCs and ANL,validating the sensitivity and specificity of the labeling method.GO analysis revealed that differentially expressed proteins were primarily involved in basic cellular biological processes such as extracellular exosome formation,extracellular matrix organization,and focal adhesion.KEGG and PPI analyses indicated that the differential proteins were mainly involved in complement and coagulation cascade pathway,actin cytoskeleton regulation pathway,and apoptosis pathway.Heatmap analysis showed significantly upregulated expression of anti-apoptosis and cell adhesion-related factors in experimental group on day 1(P＜0.05),upregulated anti-apoptotic factors,pro-apoptotic factors,and cell adhesion-related factors on day 3(P＜0.05),and upregulated anti-apoptotic factors,cell differentiation-related factors,and cell adhesion-related factors on day 7(P＜0.05)compared with control group.Expression of apoptosis-inducing factor 1 was significantly downregulated on days 1 and 7(P＜0.05).On day 3,most differentially expressed proteins,including anti-apoptosis factors(Protein S100-A11,Clusterin,Gelsolin),pro-apoptosis factor(Cathepsin B),cell differentiation-related factor(Transgelin-2),and cell adhesion-related factors(Cofilin-1,Periostin,Fibronectin)were significantly upregulated(P＜0.05).Conclusions The MetRSL247G mutation enables BMSCs to incorporate ANL and synthesize labeled proteins,confirming the feasibility of this nascent protein labeling technique.Nascent proteins of BMSCs in ischemic myocardium primarily contribute to extracellular exosome secretion and extracellular matrix organization.BMSCs may adapt to and respond to ischemic and hypoxic environments by influencing complement and coagulation cascades,activating inflammatory factors,regulating actin cytoskeleton structure,and modulating apoptosis,thereby maintaining the survival of BMSCs.