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.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher among individuals with inflammatory bowel disease (IBD) than in the general population. Emerging evidence indicates that the development of MASLD in patients with IBD may occur independently of traditional metabolic risk factors, suggesting a unique pathophysiological mechanism distinct from conventional MASLD pathways. Bile acids (BAs), which act as critical signaling molecules in enterohepatic circulation, play an essential role in maintaining gastrointestinal homeostasis through bidirectional gut–liver axis communication. These molecules are increasingly recognized as pivotal regulators in the progression of both MASLD and IBD. While previous studies have characterized the dynamics of BA in blood or fecal samples under both conditions, a comprehensive understanding of their metabolic profiles and the associated interactions within the gut–liver axis is still lacking. This review synthesizes current evidence from studies employing BA metabolomics to investigate IBD and MASLD. By focusing on BA signatures, we summarize conserved alterations between these two conditions and their potential mechanisms of disease progression. Our review advances understanding of BA-mediated pathways in IBD and MASLD, providing a foundation for assessing their roles in contributing to the pathogenesis of MASLD in patients with IBD.

BACKGROUND:Various proteins,signaling pathways,and inflammatory mediators are involved in the pathophysiological process of osteoarthritis.The development of small molecule drugs targeting these proteins,signaling pathways,and inflammatory mediators can effectively delay the progression of osteoarthritis and ameliorate its clinical manifestations. OBJECTIVE:To review the research progress of small molecule drugs in the treatment of osteoarthritis based on the pathogenesis of osteoarthritis. METHODS:PubMed,CNKI,and WanFang databases were searched with English search terms"osteoarthritis,arthritis,osteoarthrosis,degenerative,arthritides,deformans,small molecule drugs,small molecule inhibitors,small molecule agents"and Chinese search terms"osteoarthritis,small molecule drugs,small molecule inhibitors."A total of 68 articles were included for review according to the inclusion and exclusion criteria. RESULTS AND CONCLUSION:(1)Currently,studies concerning the pathogenesis of osteoarthritis remain unclear.The occurrence and development of osteoarthritis are strongly associated with proteins,cytokines,and signal transduction pathways,so its therapeutic mechanism is relatively complex.Currently,targeting proteins,cytokines,and signal transduction pathways related to osteoarthritis with small molecule drugs has become a major research focus.(2)Small molecule drugs frequently possess visible intracellular or extracellular targets and efficacy,containing enhancing cartilage repair,resisting joint degradation,attenuating inflammation,and relieving pain.Other anti-osteoarthritis small molecule drugs have shown promise in promoting stem cell chondrogenic differentiation and cartilage matrix reconstruction.(3)At present,small molecule drugs targeting the pathophysiological process of osteoarthritis to delay the progression of osteoarthritis are still in the experimental stage,but most of these small molecule drugs have shown the expected results in the experimental process,and there are no relevant studies to illustrate the efficacy of small molecule drugs in the treatment of osteoarthritis.(4)Small molecule drugs for the treatment of osteoarthritis have reached the expected experimental results in the basic experimental stage.Numerous studies have exhibited that small molecule drugs can target the suppression of specific proteins,cytokines,and signal transduction pathways that cause osteoarthritis,so as to treat osteoarthritis.Nevertheless,its safety and effectiveness still need to be identified by further basic and clinical studies.This process needs to be investigated and studied by more scholars.(5)At present,many scholars in and outside China have made contributions to the treatment of osteoarthritis.Compared with traditional treatment methods,small molecule drugs reveal better efficacy and safety in the basic experimental stage,and it is expected to become an emerging method for the treatment of osteoarthritis in the future to rid patients of pain.

[This corrects the article DOI: 10.11909/j.issn.1671-5411.2017.08.005.].

The ventral anterior (VA) nucleus of the thalamus is a major target of the basal ganglia and is closely associated with the pathogenesis of Parkinson's disease (PD). Notably, the VA receives direct innervation from the hypothalamic histaminergic system. However, its role in PD remains unknown. Here, we assessed the contribution of histamine to VA neuronal activity and PD motor deficits. Functional magnetic resonance imaging showed reduced VA activity in PD patients. Optogenetic activation of VA neurons or histaminergic afferents significantly alleviated motor deficits in 6-OHDA-induced PD rats. Furthermore, histamine excited VA neurons via H1 and H2 receptors and their coupled hyperpolarization-activated cyclic nucleotide-gated channels, inward-rectifier K⁺ channels, or Ca²⁺-activated K⁺ channels. These results demonstrate that histaminergic afferents actively compensate for Parkinsonian motor deficits by biasing VA activity. These findings suggest that targeting VA histamine receptors and downstream ion channels may be a potential therapeutic strategy for PD motor dysfunction.
Animals ; Histamine/metabolism* ; Male ; Oxidopamine/toxicity* ; Rats ; Ventral Thalamic Nuclei/physiopathology* ; Rats, Sprague-Dawley ; Disease Models, Animal ; Parkinson Disease/metabolism* ; Neurons/physiology* ; Humans ; Optogenetics

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective:To construct univariate and multivariate relapse free survival (RFS) prediction models for breast cancer patients with diabetes mellitus type 2 (T2DM) and to compare and select the model with higher predictive performance.Methods:A total of 912 breast cancer patients treated at the First Affiliated Hospital of Dalian Medical University from January 2010 to December 2016 were included, of which 202 patients had T2DM and 710 patients did not. Kaplan-Meier survival curve was drawn based on whether patients had T2DM, and log-rank test was performed based on whether patients had T2DM. All patients were randomly divided into a training set ( n=640) and a validation set ( n=272) at a ratio of 7∶3. Univariate and multivariate Cox proportional risk regression models were used to analyze RFS in breast cancer patients with the survival package. The "rms" package was employed to construct univariate and multivariate RFS prediction models for breast cancer patients with T2DM. Clinical decision curves and calibration curves were used to validate the models. The receiver operator characteristic (ROC) curve was used to compare and analyze the prediction performance of the two models. Results:There were no statistically significant differences between the training set and the validation set patients in terms of age, T2DM, surgical approach, axillary management methods, T stage, N stage, molecular sub-type, estrogen receptor (ER) 1, ER2, progesterone receptor (PR) , ER and PR consistency, Ki67, human epidermal growth factor receptor 2 (HER2) (all P>0.05) . There was a statistically significant difference in histological grade ( χ2=7.59, P=0.022) . Survival analysis showed that the 5-year RFS rate was 83.7% in patients with T2DM and 92.3% in patients without T2DM ( χ2=16.61, P<0.001) . Univariate analysis revealed that age ( HR=1.04, 95% CI: 1.03-1.06, P<0.001) , T2DM ( HR=2.31, 95% CI: 1.49-3.55, P<0.001) , surgical approach ( HR=2.39, 95% CI: 1.20-4.77, P=0.013) , axillary management methods ( HR=2.62, 95% CI: 1.72-3.98, P<0.001) , T stage (T 2: HR=2.13, 95% CI: 1.36-3.31, P<0.001; T 3: HR=6.90, 95% CI: 3.35-14.22, P<0.001) , N stage (N 2: HR=3.87, 95% CI: 2.12-7.07, P<0.001; N 3: HR=8.61, 95% CI: 4.71-15.75, P<0.001) , molecular sub-type (Luminal B: HR=2.74, 95% CI: 1.17-6.36, P=0.019; HER2 +: HR=3.64, 95% CI: 1.38-9.58, P=0.009; TNBC: HR=4.40, 95% CI: 1.71-11.34, P=0.002) , ER1 (>10%: HR=0.57, 95% CI: 0.37-0.90, P=0.016) , ER2 ( HR=0.57, 95% CI: 0.37-0.89, P=0.015) , and PR ( HR=0.56, 95% CI: 0.37-0.86, P=0.008) were all factors influencing RFS in breast cancer patients. Multivariate analysis demonstrated that age ( HR=1.04, 95% CI: 1.02-1.06, P<0.001) , T2DM ( HR=1.82, 95% CI: 1.16-2.85, P=0.009) , T stage (T 2: HR=1.60, 95% CI: 1.01-2.54, P=0.046; T 3: HR=2.64, 95% CI: 1.22-5.72, P=0.014) , N stage (N 2: HR=3.72, 95% CI: 2.01-6.88, P<0.001; N 3: HR=5.34, 95% CI: 2.78-10.25, P<0.001) , and ER1 (>10%: HR=0.63, 95% CI: 0.39-0.99, P=0.046) were independent factors influencing RFS in breast cancer patients. Based on the 10 and 5 variables with P<0.05 in the univariate and multivariate analyses respectively, the nomograms of the univariate and multivariate prediction models were constructed to evaluate the influence of factors such as T2DM on the postoperative RFS of breast cancer patients. Clinical decision curves and calibration curves indicated that both models had high predictive value for RFS in breast cancer patients, and the predictive results were highly consistent with the actual observed results. ROC curve analysis showed that there was no statistically significant difference in the area under the curve (AUC) of the two models for predicting the RFS rates of breast cancer patients in the training set and validation set at 36, 60, and 84 months (all P>0.05) , indicating that the predictive efficacy of the two models was comparable. The multivariate model is more suitable for clinical application because it uses fewer variables. Conclusions:Breast cancer patients with T2DM have poorer prognosis. Age, T2DM, T stage, N stage, and ER1 are independent factors influencing postoperative RFS in breast cancer patients. The multi-factor prediction model of RFS in breast cancer patients based on T2DM is more suitable for clinical application due to its higher predictive efficacy and fewer variables.