Objective To prepare Zanthoxylum alkaloid thermosensitive hydrogel, optimize the preparation process and conduct related performance studies. Methods Zanthoxylum alkaloids were obtained by reflux extraction, followed by enrichment and purification using macroporous adsorption resin. Poloxamer 407 and Poloxamer 188 were used as substrates to prepare the thermosensitive hydrogel of Zanthoxylum alkaloids, and the preparation process was optimized by orthogonal design. The quality of the hydrogel was systematically evaluated based on its gelation temperature, gelation time, Fourier transform infrared （FTIR） spectroscopy, scanning electron microscopy （SEM） images, mechanical properties, and in vitro release profile. Results The optimal preparation conditions for the Zanthoxylum alkaloid thermosensitive hydrogel were: 20% （g/ml） poloxamer 407, 2% （g/ml） poloxamer 188 and 100 μg/ml Zanthoxylum alkaloid. The gelation temperature was 32.6℃, and the average gelling time was 143.3 s. The hydrogel appeared as a transparent liquid at room temperature and was transformed into a semi-solid gel state when the temperature exceeded 33℃. Experimental results confirmed the successful preparation of poloxamer 407 and poloxamer 188 thermosensitive hydrogel loaded with Zanthoxylum alkaloids, which exhibited good bio adhesion, self-healing properties, and tensile strength. Conclusion The Zanthoxylum alkaloid thermosensitive hydrogel demonstrated favorable mechanical properties and a sustained-release effect, showing promising potential for further development and application.

Background Nitrosamines (NAms), emerging as disinfection by-products in drinking water, are highly carcinogenic. Given the significant NAms contamination reported in various regions of China, evaluating the contamination levels and health risks of NAms in terminal direct drinking water is of great urgency. Objective To investigate the concentration levels of NAms in piped direct drinking water at primary and secondary schools in Shanghai, and to assess the potential health risks posed to different age groups through this exposure pathway. Methods A total of 198 water samples were collected from 66 primary and secondary schools across five districts in Shanghai from May to June 2023. The mass concentrations of eight major NAms were quantified using solid-phase extraction coupled with gas chromatography-mass spectrometry (GC-MS). A carcinogenic health risk model was employed to evaluate the lifetime cancer risks associated with NAms exposure via direct drinking water for various age groups. Results Among the 198 samples, NAms were detected in 196 samples, with concentrationsranging from below the limit of detection (LOD) to 106.06 ng·L⁻¹. The average concentration of total NAms was 21.30 ng·L⁻¹, with N-nitrosodimethylamine (NDMA) exhibiting the highest detection rate at 98.5%. Significant differences in NAms concentrations were observed among water treatment systems utilizing ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO) as core processes (P<0.05). The lifetime cancer risks for different age groups ranged from 1.38×10⁻⁶ to 1.11×10⁻⁵, with NDMA contributing the most to the overall risk (82.1%). The carcinogenic risk for adults (1.08×10⁻⁵) was higher than that for children and adolescents (1.38×10⁻⁶ to 2.61×10⁻⁶). Among children and adolescents under 18 years of age, the risk decreased as age increased. Conclusion Trace levels of NAms, primarily NDMA, are detected in the piped direct drinking water at primary and secondary schools in Shanghai, with concentrations vary significantly depending on the water treatment process. The carcinogenic risks of NAms exposure via direct drinking water for all age groups are below the acceptable level (1×10⁻⁴) recommended by the U.S. Environmental Protection Agency (EPA).

Background Nitrosamines (NAms), emerging as disinfection by-products in drinking water, are highly carcinogenic. Given the significant NAms contamination reported in various regions of China, evaluating the contamination levels and health risks of NAms in terminal direct drinking water is of great urgency. Objective To investigate the concentration levels of NAms in piped direct drinking water at primary and secondary schools in Shanghai, and to assess the potential health risks posed to different age groups through this exposure pathway. Methods A total of 198 water samples were collected from 66 primary and secondary schools across five districts in Shanghai from May to June 2023. The mass concentrations of eight major NAms were quantified using solid-phase extraction coupled with gas chromatography-mass spectrometry (GC-MS). A carcinogenic health risk model was employed to evaluate the lifetime cancer risks associated with NAms exposure via direct drinking water for various age groups. Results Among the 198 samples, NAms were detected in 196 samples, with concentrationsranging from below the limit of detection (LOD) to 106.06 ng·L⁻¹. The average concentration of total NAms was 21.30 ng·L⁻¹, with N-nitrosodimethylamine (NDMA) exhibiting the highest detection rate at 98.5%. Significant differences in NAms concentrations were observed among water treatment systems utilizing ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO) as core processes (P<0.05). The lifetime cancer risks for different age groups ranged from 1.38×10⁻⁶ to 1.11×10⁻⁵, with NDMA contributing the most to the overall risk (82.1%). The carcinogenic risk for adults (1.08×10⁻⁵) was higher than that for children and adolescents (1.38×10⁻⁶ to 2.61×10⁻⁶). Among children and adolescents under 18 years of age, the risk decreased as age increased. Conclusion Trace levels of NAms, primarily NDMA, are detected in the piped direct drinking water at primary and secondary schools in Shanghai, with concentrations vary significantly depending on the water treatment process. The carcinogenic risks of NAms exposure via direct drinking water for all age groups are below the acceptable level (1×10⁻⁴) recommended by the U.S. Environmental Protection Agency (EPA).

Objective: To evaluate the diagnostic potential of fluid suppression (FS) techniques combined with amide proton transferweighted imaging (APTw) for assessment of isocitrate dehydrogenase (IDH) mutation status, glioma subtypes, and tumor proliferation. Materials and Methods: This retrospective study included 117 patients with adult-type diffuse gliomas. Conventional APTw, FSAPTw, and spillover-corrected FS-APTw (SCFS-APTw) metrics were calculated from 3T MRI data in tumor parenchyma, necrotic or cystic regions, and contralateral normal-appearing white matter. APTw signals were compared across the three techniques within each region, between IDH-mutant and IDH-wildtype gliomas, and among astrocytoma, oligodendroglioma, and glioblastoma subtypes. Diagnostic performance for distinguishing IDH mutation status and glioma subtypes was assessed using receiver operating characteristic (ROC) analysis. Correlations between APTw metrics and Ki-67 expression were also analyzed. Results: Both FS-APTw and SCFS-APTw significantly reduced signal intensity in tumor parenchyma and necrotic or cystic regions, with SCFS-APTw demonstrating a stronger suppression effect. IDH-wildtype gliomas showed significantly higher APTw metrics than IDH-mutant gliomas (all P < 0.001). Glioblastomas exhibited significantly higher metrics than oligodendrogliomas (all corrected P ≤ 0.015) and astrocytomas (all corrected P < 0.001). SCFS-APTw achieved the highest area under the ROC curve (AUC) of 0.846 for identification of IDH mutation status. For differentiation between astrocytomas and glioblastomas, the 90th percentile of APTw yielded the highest AUC (0.860), followed by SCFS-APTw (0.849). For discrimination between oligodendrogliomas and glioblastomas, the highest AUC (0.832) was obtained using the 90th percentile of SCFS-APTw. None of these metrics successfully differentiated oligodendrogliomas from astrocytomas. SCFS-APTw demonstrated the strongest correlation with Ki-67 expression (r = 0.451). Conclusion FS techniques effectively reduce elevated APTw signals originating from fluid compartments. Their combination with APTw imaging enables evaluation of IDH mutation status, glioma subtypes, and tumor proliferative activity in adulttype diffuse gliomas.

Background: This study was performed to characterize the incidence, costs, and risk factors associated with renal and cardiovascular adverse outcomes following primary percutaneous coronary intervention (pPCI) in patients with ST-elevation myocardial infarction (STEMI). Methods: Patients with STEMI who underwent pPCI using iso-osmolar contrast were enrolled at 39 centers. The incidence of acute kidney injury (AKI) and major adverse renal and cardiovascular events (MARCE) was analyzed, as well as inpatient costs. Logistic regression analysis was performed to identify risk factors. Results: Among 2,293 patients, the incidence of AKI and MARCE within 72 hours post-pPCI was 4.14% (n = 95) and 4.40% (n = 101), respectively. AKI and/or MARCE were associated with systolic blood pressure (AKI: odds ratio [OR], 1.009; 95% confidence interval [CI], 1.000–1.018), hypertension (AKI: OR, 1.815; 95% CI, 1.133–2.906; MARCE: OR, 1.760;95% CI, 1.118–2.769), anterior wall infarction (AKI: OR, 1.895; 95% CI, 1.196–3.004; MARCE:OR, 1.939; 95% CI, 1.240–3.032), Killip class (AKI: OR, 1.465; 95% CI, 1.117–1.922; MARCE:OR, 1.467; 95% CI, 1.131–1.903), and serum creatinine (SCr; MARCE: OR, 1.006; 95% CI, 1.000–1.012). Hospitalization costs for patients with STEMI who developed AKI or MARCE were significantly higher than for those without AKI (9,595 ± 5,795 vs. 8,279 ± 3,872 USD, P = 0.003) or without MARCE (9,890 ± 5,616 vs. 8,255 ± 3,859 USD, P < 0.001). Conclusions In patients with STEMI undergoing pPCI with iso-osmolar contrast, the incidence of AKI and MARCE was associated with higher hospitalization costs. Systolic blood pressure, hypertension, anterior wall infarction, Killip class, and SCr were identified as risk factors for these outcomes.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

BACKGROUND: The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM. METHODS: A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM. RESULTS: Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses. CONCLUSION The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/immunology* ; Prospective Studies ; Adult ; Inflammation/immunology* ; Glucose Tolerance Test ; Birth Cohort

Medical equipment, as an important indicator of smart hospital evaluation, plays a vital role in hospital operations. To ensure the safe and efficient operation of medical equipment, a reasonable performance evaluation system is indispensable. This study introduces a platform based on Internet of Things (IoT) technology that connects medical devices and collects data, achieving standardized and structured data processing, and supporting online operational supervision. Through the Delphi method, a performance evaluation system for large medical equipment is constructed, including 4 primary indicators and 22 secondary indicators. DICOM data acquisition devices are used to achieve functions such as efficiency analysis, benefit analysis, usage evaluation, and decision-making support for medical equipment. The study is still in its early stages, and in the future, it is expected to integrate more types of equipment, achieve rational resource allocation, and significantly impact decision-making for the development of public hospitals.
Internet of Things ; Delphi Technique

OBJECTIVE: Evaluate the clinical application effect of low-field infant MRI. METHODS: Using literature review, expert consultation, and two rounds of Delphi to determine the evaluation index system. Then retrospectively analyze and compare the data of low-field infant MRI and high-field MRI from January 2023 to December 2024. RESULTS: There is a certain gap between low-field infant MRI and high-field MRI in terms of signal-to-noise ratio, image uniformity, software system reliability, scanning time, user interface friendliness and image result consistency. However, there was no difference in terms of spatial resolution and image quality. The noise, hardware system reliability, mean time between failure and the rate of examination completed without sedation are better than that of high-field MRI. CONCLUSION Low-field infant MRI meets needs of clinical diagnostic and has stable performance. It can be used as a routine screening tool for brain diseases near the bed.
Magnetic Resonance Imaging/methods* ; Humans ; Infant ; Retrospective Studies ; Signal-To-Noise Ratio ; Reproducibility of Results ; Brain Diseases/diagnostic imaging* ; Brain/diagnostic imaging* ; Software