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.

Objective: This study characterizes the demographic and clinical profiles of patients undergoing unilateral biportal endoscopic spine surgery (UBE ESS) for lumbar decompression/discectomy at a tertiary hospital in Singapore. It examines service implementation across multiple senior surgeons, evaluates preliminary clinical outcomes, and describes the learning curve observed during early adoption among surgeons already experienced in minimally invasive spine surgery, benchmarked against international standards. In the context of increasing global uptake of endoscopic techniques, this work provides evidence to inform institutional adoption and surgeon training. This analysis forms part of a multi-paper series comparing surgeon experience and patient outcomes between conventional minimally invasive approaches and UBE ESS for lumbar decompression/discectomy. Methods: We conducted a retrospective review of 111 patients who underwent UBE lumbar decompression/discectomy at a public tertiary hospital between October 2022 and April 2024. Data on patient demographics, comorbidities, presenting symptoms, operative details, and clinical outcomes, including visual analogue scale (VAS) scores and 36-Item Short Form Health Survey (SF-36) health domains, were analyzed using appropriate statistical methods. Results: The mean patient age was 56.8 years, with a slight female predominance (54.1%). Statistically significant improvements were observed in VAS scores for both back and leg pain (p<0.05), alongside significant gains in SF-36 domains including physical functioning, bodily pain, vitality, and social functioning. Operative times decreased progressively with increasing case volume, consistent with the presence of a procedural learning curve. Conclusion UBE ESS for lumbar decompression/discectomy is a safe and efficacious technique that can be successfully adopted by spinal surgeons with prior minimally invasive surgical experience. Operative time demonstrates a meaningful reduction once the initial learning curve has been overcome. ESS provides a reproducible option for the treatment of degenerative lumbar spine disease in the tertiary hospital setting in Singapore, with outcomes comparable to established international benchmarks. Future work will include long-term follow-up of this patient cohort and direct comparison with conventional minimally invasive techniques in subsequent studies.

Objective: Spinal stenosis and degenerative spinal disorders are increasingly prevalent and have a substantial impact on quality of life. Surgical decompression, performed using either open microscopic or endoscopic approaches, remains a cornerstone of management for these conditions. This study examines evolving trends in single-level lumbar spinal decompression procedures performed at a tertiary academic hospital in Singapore. Methods: A retrospective observational study was conducted involving 588 patients who underwent single-level spinal decompression between 2021 and 2024, including endoscopic spine surgery (ESS; n=364) and microdecompression (n=224). Primary outcome measures were changes in 36-Item Short Form Health Survey (SF-36) and visual analogue scale (VAS) scores at 3 months, 6 months, and 2 years postoperatively. Secondary outcomes included length of hospital stay, reoperation rates, and operative time. Patient demographics, spinal level and pathology characteristics, surgical techniques, and postoperative outcomes were analyzed. Difference-in-differences (DID) analysis was used to compare outcomes between the 2 groups. Results: Both groups demonstrated significant postoperative improvements in SF-36 and VAS scores. At 2 years, Short Form Health Survey physical function (SFPF) scores improved in the endoscopic group (mean difference [MD], 18.6; standard deviation [SD], 21.7; p=0.064) and in the open microscopic group (MD, 36.7; SD, 20.9; p=0.007), with a non-significant DID of -18.1 (p=0.155). No DID comparisons across SF-36 domains reached statistical significance. Mean operative time for endoscopic procedures decreased from 249 minutes in 2022 to 145 minutes in 2024, reflecting a procedural learning curve. Surgeons with higher endoscopic caseloads exhibited greater improvements in functional outcomes. Conclusion Both endoscopic and open microscopic decompression achieve comparable short- and long-term clinical outcomes. ESS provides similar effectiveness while being associated with shorter recovery periods and reduced hospital stay. Further research is warranted to identify factors contributing to incomplete symptom resolution or the need for revision surgery.

Single-cell metabolite analysis at the small molecule level reveals intercellular heterogeneity and molecular diversity,especially living cell metabolite analysis which can provide more accurate biochemical information.In this study,a comprehensive single-cell metabolomics mass spectrometry analysis platform was constructed based on continuous ultrasonic sample introduction,aiming to improve the utilization rate of single cells and the efficiency of mass spectrometry detection.This platform utilized mechanical motion generated by a miniaturized ultrasound module,which minimally affected cell integrity and viability,enabling cell suspension and dispersion for up to 60 min,with cell viability exceeding 70%.By comparing cell suspension densities and the cell number of mass spectrometry detections between static and ultrasound groups,the results showed that the ultrasound treatment significantly reduced cell sedimentation rate and increased single-cell mass spectrometry detection efficiency.Applying this platform to single-cell analysis of cell line of mouse cerebellar astrocytes(C8D1A)and mouse glioma(GL261)cells achieved clustering and differential analysis of different cell types,demonstrating the method's potential in analyzing cellular heterogeneity and identifying cells.This approach promised to provide new insights and solutions for single-cell analysis.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

OBJECTIVE: Comorbid pain and depression are common but remain difficult to treat. Electroacupuncture (EA) can effectively improve symptoms of depression and relieve pain, but its neural mechanism remains unclear. Therefore, we used resting-state functional magnetic resonance imaging (rs-fMRI) to detect cerebral changes after initiating a mouse pain model via constriction of the infraorbital nerve (CION) and then treating these animals with EA. METHODS: Forty male C57BL/6J mice were divided into 4 groups: control, CION model, EA, and sham acupuncture (without needle insertion). EA was performed on the acupoints Baihui (GV20) and Zusanli (ST36) for 20 min, once a day for 10 consecutive days. The mechanical withdrawal threshold was tested 3 days after the surgery and every 3 days after the intervention. The depressive behavior was evaluated with the tail suspension test, open-field test, elevated plus maze (EPM), sucrose preference test, and marble burying test. The rs-fMRI was used to detect the cerebral changes of the functional connectivity (FC) in the mice following EA treatment. RESULTS: Compared with the CION group, the mechanical withdrawal threshold increased in the EA group at the end of the intervention (P < 0.05); the immobility time in tail suspension test decreased (P < 0.05); and the times of the open arm entry and the open arm time in the EPM increased (both P < 0.001). There was no difference in the sucrose preference or marble burying tests (both P > 0.05). The fMRI results showed that EA treatment downregulated the amplitude of low-frequency fluctuations and regional homogeneity values, while these indicators were elevated in brain regions including the amygdala, hippocampus and cerebral cortex in the CION model for comorbid pain and depression. Selecting the amygdala as the seed region, we found that the FC was higher in the CION group than in the control group. Meanwhile, EA treatment was able to decrease the FC between the amygdala and other brain regions including the caudate putamen, thalamus, and parts of the cerebral cortex. CONCLUSION EA can downregulate the abnormal activation of neurons in the amygdala and improve its FC with other brain regions, thus exerting analgesic and antidepressant effects. Please cite this article as: Yin X, Zeng XL, Lin JJ, Xu WQ, Cui KY, Guo XT, Li W, Xu SF. Brain functional changes following electroacupuncture in a mouse model of comorbid pain and depression: a resting-state functional magnetic resonance imaging study. J Integr Med. 2025; 23(2): 159-168.
Animals ; Electroacupuncture ; Male ; Magnetic Resonance Imaging ; Depression/diagnostic imaging* ; Mice, Inbred C57BL ; Brain/diagnostic imaging* ; Disease Models, Animal ; Mice ; Pain/diagnostic imaging* ; Acupuncture Points

AIM To investigate the impact of varying dosages of Supplemented Wendan Decoction on the PI3K/Akt/FOXO1 glycolipid metabolic pathway in 3T3-L1 adipocytes.METHODS The CCK-8 assay was used to determine the concentration of Supplemented Wendan Decoction-medicated serum.The mature adipocytes differentiated from 3T3-L1 preadipocytes after induction were further divided into the blank control group,the model group,the rosiglitazone group(10 mg/L),and the Supplemented Wendan Decoction groups(5％,10％,and 20％),followed by the sample collections after 48 hours of treatment.Oil red O staining quantified lipid accumulation in 3T3-L1 adipocytes;extracellular glucose levels were measured using glucose oxidase(GOD)assay;RT-qPCR analyzed mRNA expressions of IRS-1,PI3K,Akt,GLUT4,IL-6,TNF-α and IL-1β;Western blot assessed protein expressions of INSR,IRS-1,PI3K-p85,Akt,FOXO1 and GLUT4.RESULTS No significant changes in cell viability(P＞0.05)were observed in 3T3-L1 preadipocytes exposed to serum containing supplemented Wendan Decoction at different concentrations for 24,48,or 72 hours.The 3T3-L1 preadipocytes held the capacity to differentiate into mature adipocytes within a 14-day induction period.Compared to the model group,all supplemented Wendan Decoction groups exhibited reduced lipid accumulation in adipocytes and downregulated mRNA expression of IRS-1,IL-6,TNF-α and IL-1β(P＜0.01);the low-dose group demonstrated increased mRNA expressions of PI3K and GLUT4(P＜0.05,P＜0.01),alongside elevated protein expressions of INSR,IRS-1,PI3K-p85,Akt and GLUT4(P＜0.05,P＜0.01);the medium-dose group showed enhanced GLUT4 mRNA expression,and upregulated protein expressions of INSR and FOXO1(P＜0.01).After 24 hours intervention,the high-dose Supplemented Wendan Decoction group exhibited increased glucose consumption in adipocytes(P＜0.01),and elevated protein expression of INSR,Akt and FOXO1(P＜0.05,P＜0.01).CONCLUSION Supplemented Wendan Decoction reduces lipid accumulation in adipocytes,regulates glucose and lipid metabolism,and promotes metabolic homeostasis through PI3K/Akt/FOXO1 signaling pathway.