Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

ObjectiveTo develop a carbon nanoparticle-manganese dioxide (CN-MnO₂) injection integrating visually identifiable staining and magnetic resonance (MR) T₁/T₂ dual-modal imaging, and to systematically evaluate its physicochemical properties, critical quality attributes, biocompatibility, and efficacy for gastrointestinal marking and localization. MethodsCN-MnO₂ was prepared using a mild liquid-phase in situ redox deposition strategy and characterized by transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential analysis, X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). The pH of CN-MnO₂ was directly measured using a pH meter. The osmolality pressure of CN-MnO₂ was determined by the freezing point depression method. The bacterial endotoxin was detected using the gel-clot Limulus amebocyte lysate test, which did not rely on absorbance readings. The appearance of the CN-MnO₂ injection solution stored at 4 ℃ under light shielding and sealed for 0, 5, and 10 days was observed, and its hydrated particle size, polydispersity index, zeta potential, and pH were also measured. With gadopentetate dimeglumine (Gd-DTPA) as the positive control, different concentration gradients were established, and T₁ and T₂ relaxation times were measured to construct concentration-dependent plots of the longitudinal and transverse relaxation rates (R₁ and R₂) and calculate the corresponding relaxivities (r₁ and r₂), compare relaxivity performance, and determine the working concentration for subsequent in vivo experiments. Cytocompatibility was assessed using the methyl thiazolyl tetrazolium (MTT) assay and live/dead staining. Sixteen male 6-week-old SD rats were randomly assigned to an experimental group and a control group (n=8 per group) and subcutaneously injected with CN-MnO₂ injection at a total Mn concentration of 0.80 mmol/L or an equal volume of normal saline, respectively. Short-term in vivo safety was evaluated by regular body weight monitoring, hematoxylin-eosin (HE) staining of major organs, hematological and serum biochemical analyses, inflammatory cytokine detection, and inductively coupled plasma optical emission spectrometry (ICP-OES) analysis. Eight male 5–6-month-old Bama minipigs were randomly assigned to a CN-MnO₂ group (n=6) and a carbon nanoparticle suspension injection (CNSI) group (n=2). CN-MnO₂ injection or CNSI was injected subserosally into the stomach, small intestine, and colon. Within 5 min after each injection, the maximum staining diameter at each injection site was measured and recorded. MR T1WI/T2WI scans were performed on days 3 and 7 after injection to evaluate MR visualization at the injection sites. At the end of observation, the injection sites and major organs were collected for histopathological evaluation by hematoxylin-eosin staining. ResultsCN-MnO₂ appeared as a black suspension, with no obvious aggregation or sedimentation after standing at room temperature (20-25 ℃) for 15 days. Its average hydrodynamic diameter was approximately (228.7±15.3) nm, the polydispersity index was 0.184±0.021, and the zeta potential was (-24.6±2.8) mV. XPS showed that CN-MnO₂ was mainly composed of C, O, and Mn, with oxygen accounting for approximately 68.82%. The Mn 2p spectrum exhibited two characteristic peaks at 642.4 and 653.1 eV. XRD indicated that low-crystallinity δ-MnO₂ was dispersed within the carbon matrix. The pH was 6.82±0.06, the osmolality was (298.4±6.7) mOsm/kg, and the bacterial endotoxin level was below the detection limit. In vitro MR imaging showed a clear concentration-dependent response, with r₁ and r₂ values of 9.6 L·mmol^-1·s^-1 and 17.2 L·mmol^-1·s^-1, respectively, indicating favorable T₁/T₂ contrast performance superior to that of Gd-DTPA. At 0.80 mmol/L, CN-MnO₂ showed no obvious cytotoxicity in vitro. Short-term safety evaluation in SD rats revealed no obvious inflammatory response, impairment of liver or renal function, or abnormal manganese accumulation in major organs. In Bama minipigs, the mean staining diameters of the CN-MnO₂ group in the stomach, small intestine, and colon were (0.65±0.12) cm, (0.61±0.11) cm, and (0.58±0.10) cm, respectively, with no significant difference among the three injection sites (P>0.05). The overall mean staining diameter was smaller in the CN-MnO₂ group than in the CNSI group (P<0.05). MR examinations showed that the injection sites were identifiable on both day 3 and day 7, with stronger signals observed on day 3. At the end of observation, no obvious pathological abnormalities were observed at the injection sites or in major organs. ConclusionA CN-MnO₂ injection with uniform particle size and stable physicochemical properties can be successfully prepared. This formulation integrates visible gastrointestinal staining with MR T₁/T₂ dual-modal imaging, providing a new strategy for preoperative gastrointestinal marking and localization as well as precise intraoperative resection.

Epimedium sagittatum is a perennial herb of Berberidaceae. Its leaves have a long history of medicinal use in China. This plant is widely used as a Chinese traditional medicine，with the main functions of tonifying kidney Yang，strengthening bones and muscles，and dispelling wind and dampness. It can be used for treating kidney Yang deficiency，impotence，spermatorrhea，flaccidity of bones and muscles，rheumatic arthralgia，numbness，and spasms. The chemical constituents of this plant include flavonoids，polysaccharides，lignans，and alkaloids. Flavonoids are the main active ingredients. These compounds show a wide range of biological activities，including cartilage repair，anti-aging，anti-fatigue，cough-relieving，blood glucose-lowering，and anti-tumor effects. Modern pharmacological research has shown that E. sagittatum has definite pharmacological effects on the reproductive system，respiratory system，nervous system，cardiovascular system，skeletal system，etc. It has remarkable effects of helping pregnancy，resisting osteoporosis，controlling diabetes，improving immunity，and inhibiting tumor. Under the background of advocating one health and Chinese medicine，E. sagittatum is widely used in health care products，serving as the main raw material of various products. It has great market potential and is a Chinese medicinal herb with great clinical application and research value. This paper reviews the main chemical constituents and pharmacological effects of E. sagittatum based on domestic and foreign reports， providing a theoretical basis for further study on E. sagittatum and its safe clinical application.

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.

Epimedium sagittatum is a perennial herb of Berberidaceae. Its leaves have a long history of medicinal use in China. This plant is widely used as a Chinese traditional medicine，with the main functions of tonifying kidney Yang，strengthening bones and muscles，and dispelling wind and dampness. It can be used for treating kidney Yang deficiency，impotence，spermatorrhea，flaccidity of bones and muscles，rheumatic arthralgia，numbness，and spasms. The chemical constituents of this plant include flavonoids，polysaccharides，lignans，and alkaloids. Flavonoids are the main active ingredients. These compounds show a wide range of biological activities，including cartilage repair，anti-aging，anti-fatigue，cough-relieving，blood glucose-lowering，and anti-tumor effects. Modern pharmacological research has shown that E. sagittatum has definite pharmacological effects on the reproductive system，respiratory system，nervous system，cardiovascular system，skeletal system，etc. It has remarkable effects of helping pregnancy，resisting osteoporosis，controlling diabetes，improving immunity，and inhibiting tumor. Under the background of advocating one health and Chinese medicine，E. sagittatum is widely used in health care products，serving as the main raw material of various products. It has great market potential and is a Chinese medicinal herb with great clinical application and research value. This paper reviews the main chemical constituents and pharmacological effects of E. sagittatum based on domestic and foreign reports， providing a theoretical basis for further study on E. sagittatum and its safe clinical application.

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: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

OBJECTIVES: This study aims to use 3D prin-ting technology based on the principle of stereo lithography apparatus (SLA) to shape dental lithium disilicate ceramics and study the effects of different slurry proportions on the microstructure and properties of heat-treated samples. METHODS: The experimental group comprised lithium disilicate ceramics manufactured through SLA 3D printing, and the control group comprised lithium disilicate ceramics (IPS e.max CAD) fabricated through commercial milling. An array of different particle sizes of lithium disilicate ceramic powder materials (nano and micron) was selected for mixing with photocurable acrylate resin. The proportion of experimental raw materials was adjusted to prepare five groups of ceramic slurries for 3D printing (Groups S1-S5) on the basis of rheological properties, stability, and other factors. Printing, debonding, and sintering were conducted on the experimental group with the optimal ratio, followed by measurements of microstructure, crystallographic information, shrinkage, and mechanical properties. RESULTS: Five groups of lithium disilicate ceramic slurries were prepared, of which two groups with high solid content (75%) (Groups S2 and S3) were selected for 3D printing. X-ray diffraction and scanning electron microscopy results showed that lithium disilicate was the main crystalline phase in Groups S2 and S3, and its microstructure was slender, uniform, and compact. The average grain sizes of Groups S2 and S3 were (559.79±84.58) nm and (388.26±61.49) nm, respectively (P<0.05). Energy spectroscopy revealed that the samples in the two groups contained a high proportion of Si and O elements. After heat treatment, the shrinkage rate of the two groups of ceramic samples was 18.00%-20.71%. Test results revealed no statistical difference in all mechanical properties between Groups S2 and S3 (P>0.05). The flexural strengths of Groups S2 and S3 were (231.79±21.71) MPa and (214.86±46.64) MPa, respectively, which were lower than that of the IPS e.max CAD group (P<0.05). The elasticity modulus of Groups S2 and S3 were (87.40±12.99) GPa and (92.87±19.76) GPa, respectively, which did not significantly differ from that of the IPS e.max CAD group (P>0.05). The Vickers hardness values of Groups S2 and S3 were (6.53±0.19) GPa and (6.25±0.12) GPa, respectively, which were higher than that of the IPS e.max CAD group (P<0.05). The fracture toughness values of Groups S2 and S3 were (1.57±0.28) MPa·m^0.5 and (1.38±0.17) MPa·m^0.5, respectively, which did not significantly differ from that of the IPS e.max CAD group (P>0.05). CONCLUSIONS The combination of lithium disilicate ceramic powders with different particle sizes can yield a slurry with high solid content (75%) and suitable viscosity and stability. The dental lithium disilicate ceramic material is successfully prepared by using 3D printing technology. The 3D-printed samples show a small shrinkage rate after heat treatment. Their microstructure conforms to the crystal phase of lithium disilicate ceramics, and their mechanical properties are close to those of milled lithium disilicate ceramics.
Printing, Three-Dimensional ; Dental Porcelain/chemistry* ; Ceramics/chemistry* ; Materials Testing ; Particle Size