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.

ObjectiveTo evaluate the impact of yang-reinforcing and blood-activating therapy on the long-term prognosis for patients with dilated cardiomyopathy （DCM） of yang deficiency and blood stasis syndrome. MethodsA retrospective cohort study was conducted involving 371 DCM patients with yang deficiency and blood stasis syndrome. The yang-reinforcing and blood-activating therapy was defined as the exposure factor. Patients were categorized into exposure group （186 cases） and non-exposure group （185 cases） according to whether they received yang-reinforcing and blood-activating therapy combined with conventional western medicine for 6 months or longer. The follow-up period was set at 48 months， and the Kaplan-Meier survival analysis was used to assess the cumulative incidence of major adverse cardiovascular events （MACE） in both groups. Cox regression analysis was used to explore the impact of yang-reinforcing and blood-activating therapy on the risk of MACE， and subgroup analysis was performed. Changes in traditional Chinese medicine （TCM） syndrome score， left ventricular ejection fraction （LVEF）， left ventricular fractional shortening （LVFS）， left ventricular end-diastolic diameter （LVEDD）， and Minnesota Living with Heart Failure Questionnaire （MLHFQ） score were compared between groups at the time of first combined use of yang-reinforcing and blood-activating therapy （before treatment） and 1 year after receiving the therapy （after treatment）. ResultsMACE occurred in 31 cases （16.67%） in the exposure group and 47 cases （25.41%） in the non-exposure group. The cumulative incidence of MACE in the exposure group was significantly lower than that in the non-exposure group ［HR=0.559， 95%CI（0.361，0.895）， P=0.014］. Cox regression analysis showed that yang-reinforcing and blood-activating therapy was an independent factor for reducing the risk of MACE in DCM patients ［HR=0.623， 95%CI（0.396，0.980）， P=0.041］， and consistent results were observed in different subgroups. Compared with pre-treatment， the exposure group showed decreased TCM syndrome score and MLHFQ score， reduced LVEDD， and increased LVEF and LVFS after treatment （P＜0.05）； in the non-exposure group， TCM syndrome score decreased， LVEF and LVFS increased， and LVEDD reduced after treatment （P＜0.05）. After treatment， the exposure group had higher LVEF and LVFS， smaller LVEDD， and lower TCM syndrome score and MLHFQ score compared with the non-exposure group （P＜0.05）. ConclusionCombining yang-reinforcing and blood-activating therapy with conventional western medicine can reduce the risk of MACE in DCM patients with yang deficiency and blood stasis syndrome， meanwhile improving their clinical symptoms， cardiac function， and quality of life.

AIM:To investigate the associations of triglyceride glucose(TyG)index, triglyceride glucose-body mass index(TyG-BMI), and homeostatic model assessment of insulin resistance(HOMA-IR)with diabetic retinopathy(DR), and to evaluate their diagnostic value.METHODS: This study was a single-center retrospective study. Patients with type 2 diabetes mellitus(T2DM)who were hospitalized in the endocrinology department of 3201 Hospital from January 1, 2023 to March 1, 2025 were included. According to the diagnostic criteria for DR, participants were classified into DR group and non-DR(NDR)group. Then the association of TyG index, TyG-BMI, and HOMA-IR index with DR of the two groups of patients were alalyzed.RESULTS:A total of 969 patients with T2DM were enrolled in this study, including 816 patients in the DR group. Among DR group, 271 were males(33.2%)and 545 were females(66.8%), with a mean age of 56.78±11.88 years. The NDR group consisted of 153 patients, including 41 males(26.8%)and 112 females(73.2%), with a mean age of 59.40±10.52 years. Statistically significant differences were observed between the DR group and the NDR group in terms of age, BMI, TyG index, TyG-BMI, HOMA-IR index, fasting blood glucose(FBG), 2-h postprandial blood glucose(2 hPBG), fasting insulin(FINS), 2-h postprandial insulin(2 hPINS), fasting C-peptide(FCP), 2-h postprandial C-peptide(2 hPCP), total cholesterol(CHO), triglyceride(TG), low-density lipoprotein(LDL-C), blood urea nitrogen(BUN), uric acid(UA), direct bilirubin(DBIL), glycated hemoglobin(HbA1c), milligrams per total protein(M-TP), microalbuminuria(MALB), urinary albumin to creatinine ratio(UACR), 24-hour urine protein, white blood cell(WBC), neutrophil(N), and platelets(PLT; all P<0.05), while no significant differences were found in the remaining indicators(all P>0.05). In multivariable Logistic regression, both TyG index(aOR=198.65, 95% CI: 66.73-591.41, P<0.001)and TyG-BMI(aOR=1.03, 95% CI: 1.02-1.04, P<0.001)remained independently positive associated with DR. Quartile analysis indicated a progressive increase in DR risk with ascending quartiles of TyG index and TyG-BMI(all Ptrend<0.001). In contrast, HOMA-IR was not significantly associated with DR. Restricted cubic spline analysis, fully adjusted for confounders, showed a nonlinear upward trend in DR risk with increasing TyG index(Pnonlinearity<0.001), whereas TyG-BMI exhibited a U-shaped association(Pnonlinearity<0.05). No significant association was found between HOMA-IR and DR after propensity score matching. Receiver operating characteristic(ROC)curve demonstrated area under curve(AUC)values of 0.870(95% CI: 0.839-0.901)for TyG index, 0.710(95% CI: 0.665-0.755)for TyG-BMI, and 0.657(95% CI: 0.608-0.706)for HOMA-IR.CONCLUSION:The TyG index and TyG-BMI are risk factors for DR. A dose-dependent increase in DR risk was associated with elevated TyG index values. TyG-BMI exhibited an inverted U-shaped relationship with DR risk. The TyG index had better diagnostic efficiency for DR compared to both TyG-BMI and HOMA-IR index.

Objective To study the five-year survival status and influencing factors of elderly patients with lung cancer complicated with chronic obstructive pulmonary disease (COPD). Methods A cohort study was conducted to follow up 450 patients with lung cancer and chronic obstructive pulmonary disease who were hospitalized in our hospital from January 2018 to December 2023. The endpoint of the follow-up was the end of a five-year period or death. The Life Tables method was used to calculate survival rates and plot survival curves. The Cox proportional hazards model was used to analyze the influencing factors of five-year survival. Results The results indicated that the overall five-year survival rate of patients was 4.89%, and it decreased year by year. Cox regression analysis showed that age, gender, family functioning, and psychological status significantly influenced patient survival rate (all P<0.05). Stratified analysis found that the smoking status, family functioning, and psychological status of male patients all had an impact on survival rate (all P<0.05), while the psychological status of female patients had a more significant impact on survival (P=0.008). Conclusion This study provides a scientific basis for comprehensive intervention of elderly lung cancer patients with COPD. It is recommended that clinical attention should be paid to psychological and family factors to improve patient prognosis.

Objective: To explore the association between meat consumption and anxiety symptoms in first year junior high school students in Yunnan Province, and to provide theoretical support for preventing and relieving anxiety symptoms in junior high school students. Methods: From October to December 2022, a random cluster sampling method was used to select 8 500 first year junior high school students from 11 counties in Yunnan Province as the survey subjects for a questionnaire survey. The study used Food Frequency Questionnaire and the Chinese version of the Depression Anxiety Stress Scale-21 (DASS-21) to assess the meat consumption and anxiety symptoms of junior high school students.The distribution differences in anxiety symptoms among first year junior high school students with different demographic characteristics were analyzed statistically by using the Chi-square test,and the association between meat consumption and anxiety symptoms in students was analyzed by using a generalized linear model. Results: The detection rate of anxiety symptoms was 48.47%. After controlling for demographic variables and confounding factors, the consumption of livestock meat, poultry meat, processed meat, cured meat, barbecued meat and raw skin meat was statistically significant with anxiety symptoms ( β =-0.05, 0.04, 0.04, 0.08, 0.14, 0.17, all P <0.05). Stratified by ethnicity, The consumption of livestock meat, cured meat and barbecue was statistically correlated with anxiety symptoms in Han adolescents ( β =-0.07, 0.14, 0.22 ); the consumption of processed meat and raw skin meat was statistically correlated with anxiety symptoms in ethnic minority adolescents ( β =0.08, 0.18) (all P <0.05). Conclusions There is a statistical association between meat comsumption and the risk of anxiety symptoms in first year junior high school students in Yunnan Province. Guidance on meat consumption should be strengthened to prevent the occurrence of anxiety symptoms.

Radiotherapy is a crucial treatment modality for head and neck tumors. However, while effectively killing tumor cells, it significantly disrupts the homeostasis of the oral microecology, which is closely associated with various complications such as radiation-induced oral mucositis. Literature review indicates that as radiotherapy doses accumulate and treatment durations extend, the richness and diversity of the oral microbiota show a declining trend, with the genus Streptococcus decreasing most markedly. In contrast, radiotherapy selectively promotes the proliferation of bacterial phyla such as Proteobacteria and Bacteroidetes, which are rich in opportunistic pathogens. Mechanistically, radiotherapy activates the nuclear factor-kappa B pathway, triggering chronic inflammation and oxidative stress, damaging the epithelial barrier, suppressing local immunity, and causing damage to organs such as the salivary glands. It can also induce systemic diseases via the oral-gut axis, forming a multi-level, interconnected pathogenic network. In terms of interventions, treatment strategies including probiotics and prebiotics have shown promising efficacy against side effects such as radiation-induced oral mucositis. Saliva-based oral microbiota transplantation is an emerging strategy that is expected to become widely utilized for restoring oral microecological balance. Existing interventions provide preliminary pathways for clinical practice, but this field still faces several key scientific questions. The association between oral microecology and systemic diseases remains largely correlative, lacking causal evidence. Furthermore, critical parameters for oral microbiota transplantation, such as donor screening criteria, transplantation protocols, and long-term safety, are not yet well-defined. Therefore, future research should focus on conducting large-scale clinical trials to establish standardized protocols and safety evaluation systems for oral microecological interventions, and explore combined treatment therapies such as probiotics, prebiotics, and microbiota transplantation to advance the development of personalized precision modulation. These will enable more effective management of radiotherapy-induced oral microecological dysbiosis and improve treatment outcomes and quality of life for patients with head and neck tumors.

ObjectiveTo explore the molecular mechanism of aerobic exercise to improve hippocampal neuronal degeneration by regulating tryptophan metabolic pathway. Methods60 SPF-grade C57BL/6J male mice were divided into a young group (2 months old, n=30) and a senile group (12 months old, n=30), and each group was further divided into a control group (C/A group, n=15) and an exercise group (CE/AE group, n=15). An aerobic exercise program was used for 8 weeks. Learning memory ability was assessed by Y-maze, and anxiety-depression-like behavior was detected by absent field experiment. Hippocampal Trp levels were measured by GC-MS. Nissl staining was used to observe the number and morphology of hippocampal neurons, and electron microscopy was used to detect synaptic ultrastructure. ELISA was used to detect the levels of hippocampal Trp,5-HT, Kyn, KATs, KYNA, KMO, and QUIN; Western blot was used to analyze the activities of TPH2, IDO1, and TDO enzymes. ResultsGroup A mice showed significant decrease in learning and memory ability (P<0.05) and increase in anxiety and depressive behaviors (P<0.05); all of AE group showed significant improvement (P<0.05). Hippocampal Trp levels decreased in group A (P<0.05) and increased in AE group (P<0.05). Nidus vesicles were reduced and synaptic structures were degraded in group A (P<0.05), and both were significantly improved in group AE (P<0.05). The levels of Trp, 5-HT, KATs, and KYNA were decreased (P<0.05) and the levels of Kyn, KMO, and QUIN were increased (P<0.05) in group A. The activity of TPH2 was decreased (P<0.05), and the activities of IDO1 and TDO were increased (P<0.05). The AE group showed the opposite trend. ConclusionThe aging process significantly reduces the learning memory ability and increases the anxiety-depression-like behavior of mice, and leads to the reduction of the number of nidus vesicles and degenerative changes of synaptic structure in the hippocampus, whereas aerobic exercise not only effectively enhances the spatial learning memory ability and alleviates the anxiety-depression-like behavior of aging mice, but also improves the morphology and structure of neurons in hippocampal area, which may be achieved by the mechanism of regulating the tryptophan metabolic pathway.

Tumor immunotherapy has emerged as the fourth major therapeutic modality, following surgery, radiotherapy, and chemotherapy. Unlike traditional treatments that primarily target tumor cells directly, immunotherapy harnesses the body’s immune system to recognize and eliminate cancer cells. Over the past decade, various immunotherapeutic strategies have been developed, including immune checkpoint inhibitors (ICIs), chimeric antigen receptor (CAR) T cell therapy, cancer vaccines, and cytokine-based therapies. However, the immunosuppressive tumor microenvironment (TME) poses a significant obstacle to the effectiveness of these treatments. Polyamines—including putrescine, spermidine, and spermine—are polycationic metabolites that often accumulate abnormally in the TME and act as critical immunoregulatory molecules. T cells play a central role in antitumor immunity, yet their function is frequently influenced by immunoregulatory factors within the TME. Elevated polyamine levels in the TME have been implicated in dampening antitumor T cell responses, thereby facilitating tumor immune evasion. Polyamines in the TME originate from both tumor cells and tumor-associated immune cells. Tumor cells often overexpress the oncogene Myc, which drives the upregulation of polyamine biosynthetic enzymes, resulting in excessive intracellular polyamine production. Additionally, M2-polarized tumor-associated macrophages (M2-TAMs) contribute to polyamine accumulation by upregulating arginase-I (Arg-I), an enzyme that catalyzes the conversion of arginine into ornithine—a key precursor in the polyamine biosynthetic pathway. These combined sources lead to sustained polyamine enrichment in the TME, contributing to immune dysfunction and supporting tumor progression. Moreover, polyamines indirectly affect T cell activity by modulating macrophage polarization and directly suppress tumor cell apoptosis, further promoting an immunosuppressive environment. This review highlights the multifaceted roles of polyamines in modulating tumor-infiltrating T cell function, with a particular focus on their influence on CD4+ T cell differentiation,CD8+ T cell cytotoxicity, and immune checkpoint molecule expression. Recent studies suggest that polyamines suppress CD4+ T cell activation and differentiation by modulating the MAPK/ERK signaling pathway. Additionally, polyamines can impair T cell receptor (TCR) signaling and promote immune evasion through the upregulation of PD-L1 expression on tumor cells. These effects collectively contribute to weakened antitumor T cell responses. Polyamine blocking therapy (PBT), which primarily targets polyamine biosynthesis and transport, has emerged as a novel adjunctive immunotherapeutic strategy in cancer treatment. By reducing polyamine levels in the TME, PBT restores T cell effector functions and alleviates immunosuppression. Notably, studies have demonstrated that combining PBT with ICIs produces synergistic antitumor effects and may overcome resistance to ICI monotherapy. Although research has revealed the inhibitory effects of polyamines on T cell immune function, the underlying regulatory mechanisms remain to be fully elucidated. Moreover, due to compensatory mechanisms employed by tumor cells to maintain polyamine homeostasis, multi-targeted approaches may be necessary to achieve safe and effective therapeutic outcomes. Future PBT strategies may benefit from the integration of multi-omics technologies and the development of nanocarrier-based drug delivery systems, which could collectively enhance their specificity, efficacy, and applicability in cancer immunotherapy. This review systematically elucidates the immunomodulatory effects of polyamines on T cell function within the TME and provides theoretical support and novel insights for the advancement of tumor immunotherapeutic strategies.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective: To comprehensively evaluate the current alanine aminotransferase (ALT) screening strategies and provide a basis for their optimization. Methods: ALT test results of 21 345 blood samples were collected from 33 blood collection institutions. Multiple probability distribution functions were employed to fit the data, and the akaike information criterion (AIC) was used to determine the optimal fitting model. Based on this model, 1 million random samplings were conducted to simulate the final ALT test results of blood donors under different ALT screening strategies, eligibility criteria, and pre-donation ALT detection deviations. A decision tree was subsequently constructed for health economic analysis. Results: The log-normal distribution with a mean of 2.96 and a variance of 0.65 provided the best fit for the data. When the eligibility criteria was 50 U/L and the pre-donation detection deviation was ±20%, not conducting pre-donation testing increased blood donation by 1.14%. When the pre-donation detection deviation was ±20% and the eligibility criteria was raised from 50 U/L to 100 U/L, conducting and not conducting pre-donation testing increased blood donation by 7.59% and 6.60%, respectively. With a eligibility criteria of 50 U/L and a pre-donation detection deviation of ±20%, 1.14% of eligible blood donors would be disqualified from donating blood. Health economic analysis showed that when the eligibility criteria was adjusted to 56 U/L or higher, not conducting pre-donation ALT testing was the dominant strategy; under other conditions, conducting pre-donation testing was the dominant strategy. Conclusion: The selection of ALT testing strategies is a complex process influenced by multiple factors, and it is necessary to adopt an appropriate ALT screening strategy based on specific testing circumstances.