The First People's Hospital of Tianmen

This study aims to compare the effects of two 3D printed guide plates in indirect bonding and to explore the factors affecting the accuracy of transferring brackets. The study is conducted to provide experimental evidence for the design improvement of 3D printed guide plates and clinical guidance for orthodontic treatment. A total of 17 patients, including 7 females and 10 males, aged 12 to 30 years old, receiving orthodontic treatment from January 2021 to February 2024, were assigned to two groups based on consecutive enrollment. One group (n = 8) used ligature-fixed guide plates (LFGP) to bond brackets, and the other (n = 9) used jig-fixed guide plates (JFGP). Their upper and lower dental models were constructed by an intraoral scanner before and after bonding brackets. The deviations of the bracket position before and after bonding were measured in Geomagic Wrap software (version 2021.0.0.3008, 3D Systems Corporation) to compare the bracket transfer accuracy of two guide plates in occlusogingival, mesiodistal, and buccolingual dimensions. The data included middle incisors, lateral incisors, canines, the first premolars, the second premolars and the first molars. The data was analyzed in SPSS 26.0. A level of P < 0.05 was set for significance. A total of 191 brackets were bonded with LFGP, and 207 brackets were bonded with JFGP in the experiment. In the inter-group comparisons across the three-dimensional directions, significant differences were observed in the occlusogingival and buccolingual dimensions (P < 0.05). The JFGP group exhibited less deviation across these two dimensions, indicating higher precision. In the intra group comparison based on tooth classification, premolars showed significantly greater deviation compared to other tooth types in the buccolingual dimension of JFGP. Statistically significant differences were observed in the incisor-premolar and canine-premolar comparisons (P < 0.05). Both LFGP and JFGP achieved good results in accurate bracket placement in vivo, while JFGP demonstrated higher bracket transfer accuracy than LFGP in three linear dimensions.

Identifying patients at high risk of an elevated lymph node ratio (LNR) is critical for optimizing the management of nasopharyngeal carcinoma (NPC), as LNR, defined as the ratio of metastatic to examined lymph nodes, serves as a key prognostic indicator. This retrospective observational study aimed to investigate the epidemiology and influencing factors associated with high LNR in NPC patients. Various machine learning algorithms were employed to select independent predictive variables, and both univariate and multivariate Cox regression analyses were conducted to develop predictive models. The performance of different models was evaluated using receiver operating characteristic curves, calibration plots, and decision curve analysis, and nomograms and survival curves were constructed to facilitate visualization and clinical interpretation. A total of 1563 NPC patients were included in the study. The optimal model demonstrated an area under the curve of 0.73 (95% confidence interval: 0.67–0.78) in the modeling group and 0.76 (95% confidence interval: 0.70–0.81) in the validation group. The nomogram identified N stage, M stage, type of surgery, race, and confirmation status as independent risk factors for high LNR. Survival curve analysis further indicated that patients classified as high-risk by the nomogram had significantly worse outcomes. These findings suggest that elevated LNR is strongly associated with adverse prognosis in NPC patients. The constructed nomogram serves as a practical clinical tool to stratify patients based on LNR risk, thereby enabling personalized follow-up, treatment planning, and management strategies to optimize patient outcomes.

BackgroundEarly-onset preeclampsia (EOPE) is associated with placental malperfusion and systemic endothelial dysfunction. Maternal immune dysregulation has been implicated in EOPE, but immune findings obtained during severe disease are descriptive and do not define a validated EOPE subtype.Case presentationA 22-year-old woman (G2P0) with a monochorionic diamniotic twin pregnancy developed gestational hypertension at 25+5 weeks and met criteria for EOPE at 30–31 weeks. Because of refractory progression under standard management, immune testing obtained at 31+1 weeks showed elevated TNF-α, low complement C4, weak ANA positivity, and T/B-cell imbalance (descriptive findings in this single case). After multidisciplinary discussion and informed consent for off-label therapy in pregnancy, an immunomodulatory regimen was started at 31+1 weeks (prednisone 10 mg/day, hydroxychloroquine 200 mg bid, and a single 200 mg SC dose of certolizumab pegol). Over the subsequent week, proteinuria decreased by >50% (10.78 to 4.99 g/24 h), blood pressure improved to 100–120/60–80 mmHg, and edema regressed. Gestation continued until 35+0 weeks, when cesarean delivery was performed for fetal compromise (Type II sFGR with umbilical-artery AEDF). Placental pathology showed multifocal infarctions and basal-plate fibrinoid deposition.DiscussionEOPE likely involves heterogeneous pathways in which inflammatory mediators, complement dysregulation, and cytokine excess have been reported. This case is hypothesis-generating and highlights the need for validated immune/angiogenic stratification and prospective evaluation of any adjunctive immunomodulatory approach in severe EOPE.ConclusionIn this single MCDA twin pregnancy complicated by severe EOPE and concurrent immune-activation markers, initiation of a pregnancy-compatible immunomodulatory regimen was temporally associated with maternal clinical stabilization and a 3–4-week interval to delivery for fetal indications. Controlled studies with validated phenotyping, serial biomarkers (including sFlt-1/PlGF), standardized endpoints, and detailed safety follow-up are needed before attributing benefit or recommending this approach.

The microstructure and properties of gray cast iron are closely related. For gray cast iron with pearlite matrix, adjusting graphite characteristics to improve casting performance is the most effective method. It is of great significance to analyze the relationship between graphite characteristics and properties of gray cast iron for the development of gray cast iron with high tensile strength and high thermal conductivity. Regression models of graphite characteristics and properties of gray cast iron was established, including tensile strength and thermal conductivity. By calculating the coefficients of the two models, the different effects of graphite characteristics on the properties of gray cast iron were obtained. By testing the regression models, the feasibility of the regression analysis method in the performance analysis of gray iron castings was determined. According to the analysis results, some improvement schemes are put forward to improve the performance of castings.

To address uncertain demand during the pandemic, hospitals have utilized supply chain strategies by coordinating their available medical service capacity laterally. In this coordination, hospitals either request medical service capacity from external sources or mobilize part of their own capacity to support other hospitals, which influences the latter’s capacity decisions. Optimizing these lateral coordination strategies and addressing challenges such as oversupply and inequity are critical issues in collaborative hospital responses. This paper examines how hospitals adjust their medical service capacity and transshipment capacity through proactive and reactive policies under the leveraging scheme of the Integrated County Healthcare Consortium (ICHC). We find that ICHC strategy decisions are influenced not only by demand size and the gap between hospitals but also by demand fluctuations. Additionally, even if hospitals engage in lateral coordination, their roles — either as a receiver or a source — are affected by both demand uncertainty and the ICHC’s leveraging scheme. Regarding equity, we identify a hump-shaped relationship between the leveraging scheme of the ICHC, the quantity of service capacity transshipped, and equity. We propose a more balanced solution where the ICHC sets a scheme that allows the receiving hospital to dominate coordination decisions, thus benefiting both economic outcomes and equity.

Extracapsular extension (ECE) of prostate cancer (PCa) is a crucial determinant for preoperative staging, significantly influencing urologists’ surgical planning. While magnetic resonance imaging (MRI) aids staging by depicting ECE, its diagnostic accuracy is frequently constrained by poor image quality. Deep learning-based diffusion-weighted imaging (DL-DWI) holds potential for enhancing diagnostic accuracy through improved image quality. This multicenter retrospective study enrolled 252 consecutive patients with clinically suspected PCa from five centers between June 2019 and September 2023. All patients underwent multiparametric MRI (mpMRI) followed by radical prostatectomy. A denoising diffusion probabilistic model (DDPM) was developed to synthesize high-b-value DL-DWI images. Two radiologic residents independently evaluated the image quality of DL-DWI and conventionally obtained DWI (C-DWI) using a five-point Likert scale. Objective image quality metrics including estimated signal-to-noise ratio (eSNR), contrast-to-noise ratio (CNR), edge rise distance (ERD), and edge rise slope (ERS) were quantitatively assessed and compared between sequences. Four radiologists (experience range: 2–20 years) independently made the diagnosis of each patient based on the DL-DWI and C-DWI using the four-scale ECE grade system. Intra-reader agreement was assessed using weighted kappa, and inter-reader agreement using Fleiss’ kappa. Diagnostic performance was compared using multi-reader multi-case receiver operating characteristic analysis, with the area under the curve (AUC) as the metric. Decision curve analysis (DCA) evaluated the net clinical benefit. Statistical significance was defined as a two-sided P < 0.05. DL-DWI demonstrated significantly superior image quality compared to C-DWI (P < 0.05) and higher agreement for both intra-reader (weighted κ: 0.59, 0.45 vs. 0.40, 0.33 for readers 1 and 2, respectively) and inter-reader (weighted κ: 0.59 vs. 0.48) quality assessments. Quantitative analysis confirmed substantial improvement in DL-DWI across all objective metrics: eSNR (56.66 ± 7.36 vs. 31.76 ± 12.97, P < 0.001), CNR (28.89 ± 9.27 vs. 10.53 ± 5.48, P < 0.001), ERD (2.85 [IQR:1.90–3.80] vs. 4.27 [IQR:3.27–5.60], P < 0.001), and ERS (69.48 ± 19.15 vs. 23.82 ± 10.29, P < 0.001). For ECE detection, DL-DWI showed higher intra-reader agreement (weighted κ for readers 3–6: 0.53, 0.56, 0.67, 0.70 vs. 0.53, 0.34, 0.52, 0.49) and inter-reader agreement (Fleiss κ: 0.25 vs. 0.18) compared to C-DWI. DL-DWI achieved significantly higher diagnostic performance (mean AUC: 0.76 [95% CI: 0.71–0.80] vs. 0.70 [95% CI: 0.65–0.74], P < 0.001). DCA indicated greater net clinical benefit for DL-DWI compared to C-DWI. DL-DWI appears to outperform C-DWI in both image quality and clinical utility, showing potential to improve ECE diagnostic accuracy for residents, enhance inter-reader consistency, and provide greater net benefit in clinical decision-making. Not applicable.

This study aimed to develop and validate a predictive model for differentiating central from peripheral etiologies in patients with isolated vestibular syndrome (VS). In this multicenter retrospective cohort study, 506 patients with isolated VS from five hospitals were divided into derivation (n = 301) and validation (n = 205) cohorts. Multivariable logistic regression was performed to determine independent predictors of central VS. These predictors were assigned weights to construct the SAV3E score. The performance of the SAV3E was assessed using the area under the curve (AUC), calibration, and decision curve analysis (DCA) and compared with that of the TriAGe+ and STANDING models. The SAV3E score incorporated five predictors: absence of vestibular vagal symptoms (OR, 0.233; 95% CI, 0.084-0.648; p = 0.005), prior stroke (OR, 15.204; 95% CI, 4.455-51.884; p < 0.001), ABCD2 score of 4-7 (OR, 1.903; 95% CI, 1.206-3.004; p = 0.006), central video oculography nystagmus (OR, 38.377; 95% CI, 8.631-170.644; p < 0.001), and positive video head impulse test (OR, 0.078; 95% CI, 0.033-0.188; p < 0.001). It displayed good discriminative performance with AUCs 0.910 and 0.886 in the derivation and validation cohorts, respectively. It outperformed TriAGe+ (AUC: 0.706) and STANDING (AUC: 0.779) models. Furthermore, calibration analysis revealed good model fit across cohorts (Hosmer-Lemeshow test results: derivation cohort, p = 0.899; validation cohort, p = 0.789). DCA confirmed good clinical utility across a wide range of probability thresholds (derivation cohort: 0.01-0.86, validation cohort: 0.01-1.00). The SAV3E score is a validated tool aimed at differentiating central versus peripheral VS, with the potential to improve diagnostic accuracy for urgent etiologies such as stroke.

Non-small-cell lung cancer (NSCLC) frequently harbors EGFR mutations, with the L858R and exon 19 deletions being the most prevalent. Rare EGFR exon 18 mutations, such as E709K, account for a small proportion but may significantly influence treatment response. The coexistence of E709K and L858R mutations presents unique therapeutic challenges and opportunities. This report describes a 64-year-old Chinese woman diagnosed with advanced lung adenocarcinoma harboring concurrent EGFR mutations (exon 18 p.E709K and exon 21 p.L858R). Initial treatment with osimertinib achieved partial response with a progression-free survival of 8 months, followed by disease progression. The patient was subsequently treated with afatinib, which showed transient efficacy but was discontinued due to poor tolerance. Combination therapies involving chemotherapy (paclitaxel-platinum and pemetrexed), bevacizumab, radiotherapy and the third-generation EGFR TKI amitinib were sequentially administered, resulting in sustained symptomatic relief and clinical benefit. Leptomeningeal metastasis was later managed with intrathecal pemetrexed and ongoing amitinib therapy. In conclusion, this case highlights the complex clinical course of NSCLC with dual EGFR mutations, including E709K. While first- and second-generation TKIs offer variable efficacy, third-generation TKIs like amitinib may provide a durable benefit in selected patients. Comprehensive genomic profiling and individualized therapeutic strategies are essential for optimizing outcomes, particularly in cases involving rare EGFR mutations.