Background In 2021, chronic obstructive pulmonary disease (COPD) emerged as the forth leading cause of death in the world. However, the impact of air pollutants on COPD is still inconsistent across current studies. Objective To analyze the relationship between ambient sulfur dioxide (SO₂) exposure and hospital admissions for COPD in Lanzhou, and to examine the modified effects of SO₂ across different genders, age groups, and seasons. Methods A total of 20718 hospital admission records for COPD were collected from Lanzhou between 2016 and 2020, alongside synchronized data on SO₂ concentration and meteorological variables. A generalized additive model integrated with a distributed lag nonlinear model was used to assess the relationship and the lag effects between SO₂ exposure and COPD admissions. Potential confounders, including meteorological factors, day-of-the-week effect, and holidays, were controlled for, with a maximum lag period set at 7 d. Two-pollutant models and sensitivity analyses were conducted to ensure robustness. Results are expressed as relative risks (RR) with 95% confidence intervals (95%CI). Results During the study period, the average daily number of COPD admissions was 11.34±7.03. The average mass concentration of SO₂ was (23.72±12.35) μg·m⁻³. SO₂ exposure was positively correlated with COPD admissions; specifically, each 10 μg·m⁻³ increase in SO₂ concentration was associated with an RR of 1.440 (95%CI: 1.317, 1.573). Stratified analyses found that at a cumulative lag of 7 d, the RRs were higher among females, individuals aged ≥65 years, and during the cold season. Conversely, no significant increase in COPD admission risk related to SO₂ was observed during the warm season. For every 10 μg·m⁻³ increase in SO₂ concentration, the RR was 1.483 (95%CI: 1.311, 1.678) for females, 1.441 (95%CI: 1.311, 1.583) for those aged > 65 years， and 1.595 (95%CI: 1.313, 1.937) during the cold season. Conclusion Short-term exposure to ambient SO₂ exposure in Lanzhou is associated with an increased risk of COPD admission. The association is more pronounced among females, the elderly (aged> 65 years) and during the cold season.

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.

Purpose: Metastatic rectal cancer (mRC) is a highly lethal and complex disease that demands a multidisciplinary treatment approach. However, the clinical effectiveness of radiotherapy (RT) for de novo mRC remains controversial and uncertain. Methods: This retrospective cohort study examined medical records from Kaohsiung Chang Gung Memorial Hospital for patients with histologically confirmed de novo mRC diagnosed between January 2015 and December 2020. All patients received standard systemic therapy and radical surgery when feasible. The primary outcome, overall survival (OS), was assessed using the Kaplan-Meier method. Multivariable analysis was performed using a Cox regression model. Results: Among 271 patients included in the analysis, 117 received RT and 154 did not. The median OS was significantly longer in the RT group compared with the non-RT group (27.8 months vs. 21.9 months; P=0.046). Multivariate analysis identified several independent predictors of OS: age ≥65 years (hazard ratio [HR], 1.69; 95% confidence interval [CI], 1.26–2.27; P=0.001), primary tumor resection (HR, 2.62; 95% CI, 1.90–3.61; P<0.001), M1b or M1c disease (HR, 1.97; 95% CI, 1.44–2.69; P<0.001), and receipt of RT (HR, 1.41; 95% CI, 1.02–1.94; P=0.036). Conclusion RT significantly improves OS in patients with mRC, underscoring its role in treatment strategies. These findings support its inclusion in therapeutic protocols and highlight the need for larger, multicenter trials to confirm and extend these results.

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.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective To analyze the trends in the disease burden of schistosomiasis in China from 1992 to 2021, and to project the disease burden of schistosomiasis in China from 2022 to 2030, so as to provide insights into the elimination of schistosomiasis in China. Methods The prevalence, age-standardized prevalence, disability-adjusted life year (DALYs) rate and age-standardized DALYs rate of schistosomiasis, as well as the years lost due to disability (YLDs) rate and age-standardized YLDs rate of anemia attributable to Schistosoma infections in China, the world and different socio-demographic index (SDI) regions were captured from the Global Burden of Disease Study 2021 (GBD 2021) data resources, and the trends in the disease burden due to schistosomiasis were evaluated with estimated annual percentage change (EAPC) and its 95% confidence interval (CI). In addition, the age, period and cohort effects on the prevalence of schistosomiasis were examined in China using an age-period-cohort (APC) model, and the disease burden of schistosomiasis was predicted in China from 2022 to 2030 using a Bayesian age-period-cohort (BAPC) model. Results The age-standardized prevalence and DALYs rate of schistosomiasis, and the age-standardized YLDs rate of anemia attributable to Schistosoma infections were 761.32/10⁵, 5.55/10⁵ and 0.38/10⁵ in China in 2021. These rates were all lower than the global levels (1 914.30/10⁵, 21.90/10⁵ and 3.36/10⁵, respectively), as well as those in the medium SDI regions (1 413.61/10⁵, 12.10/10⁵ and 1.93/10⁵, respectively), low-medium SDI regions (2 461.03/10⁵, 26.81/10⁵ and 4.48/10⁵, respectively), and low SDI regions (5 832.77/10⁵, 94.48/10⁵ and 10.65/10⁵, respectively), but higher than those in the high SDI regions (59.47/10⁵, 0.49/10⁵ and 0.05/10⁵, respectively) and high-medium SDI regions (123.11/10⁵, 1.20/10⁵ and 0.12/10⁵, respectively). The prevalence and DALYs rate of schistosomiasis were higher among men (820.79/10⁵ and 5.86/10⁵, respectively) than among women (697.96/10⁵ and 5.23/10⁵, respectively) in China in 2021, while the YLDs rate of anemia attributable to Schistosoma infections was higher among women (0.66/10⁵) than among men (0.12/10⁵). The prevalence of schistosomiasis peaked at ages of 30 to 34 years among both men and women, while the DALYs rate of schistosomiasis peaked among men at ages of 15 to 19 years and among women at ages of 20 to 24 years. The age-standardized prevalence of schistosomiasis showed a moderate decline in China from 1992 to 2021 relative to different SDI regions [EAPC = -1.51%, 95% CI: (-1.65%, -1.38%)], while the age-standardized DALYs rate [EAPC = -3.61%, 95% CI: (-3.90%, -3.33%)] and age-standardized YLDs rate of anemia attributable to Schistosoma infections [EAPC = -4.16%, 95% CI: (-4.38%, -3.94%)] appeared the fastest decline in China from1992 to 2021 relative to different SDI regions. APC modeling showed age, period, and cohort effects on the trends in the prevalence of schistosomiasis in China from 1992 to 2021, and the prevalence of schistosomiasis appeared a rise followed by decline with age, and reduced with period and cohort. BAPC modeling revealed that the age-standardized prevalence and age-standardized DALYs rate of schistosomiasis, and age-standardized YLDs rate of anemia attributable to Schistosoma infections all appeared a tendency towards a decline in China from 2022 to 2030, which reduced to 722.72/10⁵ [95% CI: (538.74/10⁵, 906.68/10⁵)], 5.19/10⁵ [95% CI: (3.54/10⁵, 6.84/10⁵)] and 0.30/10⁵ [95% CI: (0.21/10⁵, 0.39/10⁵)] in 2030, respectively. Conclusions The disease burden of schistosomiasis appeared a tendency towards a decline in China from 1992 to 2021, and is projected to appear a tendency towards a decline from 2022 to 2030. There are age, period and cohort effects on the prevalence of schistosomiasis in China. Precision schistosomiasis control is required with adaptations to current prevalence and elimination needs.

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.